morph-locations-final
Allison Davis Connelly
2024-02-24
Data collection
## Using libcurl 8.3.0 with Schannel##
## Attaching package: 'dplyr'## The following objects are masked from 'package:stats':
##
## filter, lag## The following objects are masked from 'package:base':
##
## intersect, setdiff, setequal, union## `geom_smooth()` using formula = 'y ~ x'
Location effects
Will run an ANOVA on the residuals with location and species as fixed effects. This will show me if morphology depends on the species, the location, and if the location and species interact to determine morphology. CANNOT DO WITH COUNT DATA–may have to run a glmer with zero-tuncated negative binomial/quasi-poisson distribution instead (think this will tell me if species, location, and interaction affect the trait…). Will only work with the residuals, because comparing the means of the residuals indicates differences in variation. Would I not just use Levene’s and MWU again but include spp and zone/basin/watershed?
Leaving the anovas for count data in rn until I figure out what to do.
I will first run this using the zones as the location factor. Zones (1-4) represent the latitude range with equivalent sample sizes in each, since the collections were not equally representative of all latitudes, and I wanted to avoid a sampling bias when randomly selecting samples. Zone 1 corresponds to the southern most latitude range, and zone 4 corresponds to the northern most latitude range.
I will then run the same analysis using basin as the location factor. Since fish are physically isolated to the river basins they occupy, the genetic variation is also limited to that basin. Thus it is possible for fish within the same basin to be more similar due to genetic/physical constraints. (will also do with watershed just to see).
Lastly I will run ANOVAs with both zones and basins but with standardized residuals. This would allow me to compare overall variation across traits (at least those that are depended on body size) rather than just one trait at a time. Not 100% sure if this is useful (or correct to do), but thought it would be interesting.
All data
ANOVAs
Amazon
Zones
library(ggplot2)
lat3 <- raw2[raw2$SPP == "p.latipinna", ]
form3 <- raw2[raw2$SPP == "p.latipinna", ]
A.D.F <- aov(abs.res.D ~ QUARTILE, data=form3)
summary(A.D.F)## Df Sum Sq Mean Sq F value Pr(>F)
## QUARTILE 3 2.306 0.7685 4.292 0.00635 **
## Residuals 130 23.277 0.1791
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1ggplot(form3, aes(x=factor(QUARTILE), y=abs.res.D)) +
geom_boxplot()
A.P1.F <- aov(abs.res.P1 ~ QUARTILE, data=form3)
summary(A.P1.F)## Df Sum Sq Mean Sq F value Pr(>F)
## QUARTILE 3 0.159 0.05296 0.444 0.722
## Residuals 130 15.511 0.11932A.P1.R.F <- aov(abs.res.P1.R ~ QUARTILE, data=form3)
summary(A.P1.R.F)## Df Sum Sq Mean Sq F value Pr(>F)
## QUARTILE 3 0.065 0.02172 0.166 0.919
## Residuals 130 16.987 0.13067ggplot(form3, aes(x=factor(QUARTILE), y=abs.res.P1.R)) +
geom_boxplot()
A.LLSC.F <- aov(abs.res.LLSC ~ QUARTILE, data=form3)
summary(A.LLSC.F)## Df Sum Sq Mean Sq F value Pr(>F)
## QUARTILE 3 1.31 0.4354 1.209 0.309
## Residuals 130 46.80 0.3600A.SBLL.F <- aov(abs.res.SBLL ~ QUARTILE, data=form3)
summary(A.SBLL.F)## Df Sum Sq Mean Sq F value Pr(>F)
## QUARTILE 3 0.436 0.1454 1.142 0.335
## Residuals 130 16.546 0.1273ggplot(form3, aes(x=factor(QUARTILE), y=abs.res.SBLL)) +
geom_boxplot()
A.BD.F <- aov(abs.res.BD ~ QUARTILE, data=form3)
summary(A.BD.F)## Df Sum Sq Mean Sq F value Pr(>F)
## QUARTILE 3 0.00594 0.001981 1.519 0.213
## Residuals 130 0.16955 0.001304ggplot(form3, aes(x=factor(QUARTILE), y=abs.res.BD)) +
geom_boxplot()
A.CPD.F <- aov(abs.res.CPD ~ QUARTILE, data=form3)
summary(A.CPD.F)## Df Sum Sq Mean Sq F value Pr(>F)
## QUARTILE 3 0.01249 0.004163 6.832 0.00026 ***
## Residuals 130 0.07922 0.000609
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1ggplot(form3, aes(x=factor(QUARTILE), y=abs.res.CPD)) +
geom_boxplot()
A.CPL.F <- aov(abs.res.CPL ~ QUARTILE, data=form3)
summary(A.CPL.F)## Df Sum Sq Mean Sq F value Pr(>F)
## QUARTILE 3 0.02074 0.006912 9.448 1.08e-05 ***
## Residuals 130 0.09511 0.000732
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1ggplot(form3, aes(x=factor(QUARTILE), y=abs.res.CPL)) +
geom_boxplot()
A.PreDL.F <- aov(abs.res.PreDL ~ QUARTILE, data=form3)
summary(A.PreDL.F)## Df Sum Sq Mean Sq F value Pr(>F)
## QUARTILE 3 0.00209 0.0006977 1.606 0.191
## Residuals 130 0.05646 0.0004343ggplot(form3, aes(x=factor(QUARTILE), y=abs.res.PreDL)) +
geom_boxplot()
A.DbL.F <- aov(abs.res.DbL ~ QUARTILE, data=form3)
summary(A.DbL.F)## Df Sum Sq Mean Sq F value Pr(>F)
## QUARTILE 3 0.01219 0.004063 2.276 0.0828 .
## Residuals 130 0.23204 0.001785
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1ggplot(form3, aes(x=factor(QUARTILE), y=abs.res.DbL)) +
geom_boxplot()
A.HL.F <- aov(abs.res.HL ~ QUARTILE, data=form3)
summary(A.HL.F)## Df Sum Sq Mean Sq F value Pr(>F)
## QUARTILE 3 0.00344 0.0011466 1.324 0.269
## Residuals 130 0.11260 0.0008661ggplot(form3, aes(x=factor(QUARTILE), y=abs.res.HL)) +
geom_boxplot()
A.HD.F <- aov(abs.res.HD ~ QUARTILE, data=form3)
summary(A.HD.F)## Df Sum Sq Mean Sq F value Pr(>F)
## QUARTILE 3 0.00672 0.002239 2.04 0.111
## Residuals 130 0.14269 0.001098A.HW.F <- aov(abs.res.HW ~ QUARTILE, data=form3)
summary(A.HW.F)## Df Sum Sq Mean Sq F value Pr(>F)
## QUARTILE 3 0.01136 0.003788 7.212 0.000163 ***
## Residuals 130 0.06827 0.000525
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1ggplot(form3, aes(x=factor(QUARTILE), y=abs.res.HW)) +
geom_boxplot()
A.SnL.F <- aov(abs.res.SnL ~ QUARTILE, data=form3)
summary(A.SnL.F)## Df Sum Sq Mean Sq F value Pr(>F)
## QUARTILE 3 0.00766 0.0025545 5.052 0.00242 **
## Residuals 130 0.06573 0.0005056
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1A.OL.F <- aov(abs.res.OL ~ QUARTILE, data=form3)
summary(A.OL.F)## Df Sum Sq Mean Sq F value Pr(>F)
## QUARTILE 3 2.17e-32 7.242e-33 1.538 0.208
## Residuals 130 6.12e-31 4.708e-33ggplot(form3, aes(x=factor(QUARTILE), y=abs.res.OL)) +
geom_boxplot()
Basins
A1.D.F <- aov(abs.res.D ~ BASIN, data=form3)
summary(A1.D.F)## Df Sum Sq Mean Sq F value Pr(>F)
## BASIN 5 2.789 0.5579 3.133 0.0106 *
## Residuals 128 22.793 0.1781
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1ggplot(form3, aes(x=factor(BASIN), y=abs.res.D)) +
geom_boxplot()
A1.P1.F <- aov(abs.res.P1 ~ BASIN, data=form3)
summary(A1.P1.F)## Df Sum Sq Mean Sq F value Pr(>F)
## BASIN 5 0.945 0.1891 1.643 0.153
## Residuals 128 14.725 0.1150A1.P1.R.F <- aov(abs.res.P1.R ~ BASIN, data=form3)
summary(A1.P1.R.F)## Df Sum Sq Mean Sq F value Pr(>F)
## BASIN 5 0.159 0.03187 0.241 0.943
## Residuals 128 16.893 0.13197ggplot(form3, aes(x=factor(BASIN), y=abs.res.P1.R)) +
geom_boxplot()
A1.LLSC.F <- aov(abs.res.LLSC ~ BASIN, data=form3)
summary(A1.LLSC.F)## Df Sum Sq Mean Sq F value Pr(>F)
## BASIN 5 4.54 0.9080 2.668 0.025 *
## Residuals 128 43.57 0.3404
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1ggplot(form3, aes(x=factor(BASIN), y=abs.res.LLSC)) +
geom_boxplot()
A1.SBLL.F <- aov(abs.res.SBLL ~ BASIN, data=form3)
summary(A1.SBLL.F)## Df Sum Sq Mean Sq F value Pr(>F)
## BASIN 5 0.755 0.1510 1.191 0.317
## Residuals 128 16.228 0.1268ggplot(form3, aes(x=factor(BASIN), y=abs.res.SBLL)) +
geom_boxplot()
A1.BD.F <- aov(abs.res.BD ~ BASIN, data=form3)
summary(A1.BD.F)## Df Sum Sq Mean Sq F value Pr(>F)
## BASIN 5 0.00786 0.001571 1.2 0.313
## Residuals 128 0.16764 0.001310ggplot(form3, aes(x=factor(BASIN), y=abs.res.BD)) +
geom_boxplot()
A1.CPD.F <- aov(abs.res.CPD ~ BASIN, data=form3)
summary(A1.CPD.F)## Df Sum Sq Mean Sq F value Pr(>F)
## BASIN 5 0.01713 0.003425 5.879 6.34e-05 ***
## Residuals 128 0.07458 0.000583
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1ggplot(form3, aes(x=factor(BASIN), y=abs.res.CPD)) +
geom_boxplot()
A1.CPL.F <- aov(abs.res.CPL ~ BASIN, data=form3)
summary(A1.CPL.F)## Df Sum Sq Mean Sq F value Pr(>F)
## BASIN 5 0.02013 0.004025 5.383 0.000159 ***
## Residuals 128 0.09572 0.000748
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1A1.PreDL.F <- aov(abs.res.PreDL ~ BASIN, data=form3)
summary(A1.PreDL.F)## Df Sum Sq Mean Sq F value Pr(>F)
## BASIN 5 0.00492 0.0009846 2.35 0.0445 *
## Residuals 128 0.05363 0.0004190
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1ggplot(form3, aes(x=factor(BASIN), y=abs.res.PreDL)) +
geom_boxplot()
A1.DbL.F <- aov(abs.res.DbL ~ BASIN, data=form3)
summary(A1.DbL.F)## Df Sum Sq Mean Sq F value Pr(>F)
## BASIN 5 0.00996 0.001992 1.088 0.37
## Residuals 128 0.23428 0.001830ggplot(form3, aes(x=factor(BASIN), y=abs.res.DbL)) +
geom_boxplot()
A1.HL.F <- aov(abs.res.HL ~ BASIN, data=form3)
summary(A1.HL.F)## Df Sum Sq Mean Sq F value Pr(>F)
## BASIN 5 0.00766 0.0015321 1.809 0.115
## Residuals 128 0.10838 0.0008467ggplot(form3, aes(x=factor(BASIN), y=abs.res.HL)) +
geom_boxplot()
A1.HD.F <- aov(abs.res.HD ~ BASIN, data=form3)
summary(A1.HD.F)## Df Sum Sq Mean Sq F value Pr(>F)
## BASIN 5 0.00684 0.001367 1.228 0.3
## Residuals 128 0.14257 0.001114ggplot(form3, aes(x=factor(BASIN), y=abs.res.HD)) +
geom_boxplot()
A1.HW.F <- aov(abs.res.HW ~ BASIN, data=form3)
summary(A1.HW.F)## Df Sum Sq Mean Sq F value Pr(>F)
## BASIN 5 0.01460 0.0029194 5.746 8.11e-05 ***
## Residuals 128 0.06504 0.0005081
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1ggplot(form3, aes(x=factor(BASIN), y=abs.res.HW)) +
geom_boxplot()
A1.SnL.F <- aov(abs.res.SnL ~ BASIN, data=form3)
summary(A1.SnL.F)## Df Sum Sq Mean Sq F value Pr(>F)
## BASIN 5 0.01931 0.003861 9.138 1.87e-07 ***
## Residuals 128 0.05409 0.000423
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1A1.OL.F <- aov(abs.res.OL ~ BASIN, data=form3)
summary(A1.OL.F)## Df Sum Sq Mean Sq F value Pr(>F)
## BASIN 5 1.240e-32 2.479e-33 0.511 0.768
## Residuals 128 6.214e-31 4.854e-33ggplot(form3, aes(x=factor(BASIN), y=abs.res.OL)) +
geom_boxplot()
Watersheds
A2.D.F <- aov(abs.res.D ~ WATERSHED, data=form3)
summary(A2.D.F)## Df Sum Sq Mean Sq F value Pr(>F)
## WATERSHED 11 3.847 0.3497 1.963 0.0378 *
## Residuals 122 21.736 0.1782
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1ggplot(form3, aes(x=factor(WATERSHED), y=abs.res.D)) +
geom_boxplot()
A2.P1.F <- aov(abs.res.P1 ~ WATERSHED, data=form3)
summary(A2.P1.F)## Df Sum Sq Mean Sq F value Pr(>F)
## WATERSHED 11 1.302 0.1184 1.005 0.446
## Residuals 122 14.368 0.1178A2.P1.R.F <- aov(abs.res.P1.R ~ WATERSHED, data=form3)
summary(A2.P1.R.F)## Df Sum Sq Mean Sq F value Pr(>F)
## WATERSHED 11 0.34 0.03093 0.226 0.995
## Residuals 122 16.71 0.13698ggplot(form3, aes(x=factor(WATERSHED), y=abs.res.P1.R)) +
geom_boxplot()
A2.LLSC.F <- aov(abs.res.LLSC ~ WATERSHED, data=form3)
summary(A2.LLSC.F)## Df Sum Sq Mean Sq F value Pr(>F)
## WATERSHED 11 8.16 0.7422 2.267 0.015 *
## Residuals 122 39.94 0.3274
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1ggplot(form3, aes(x=factor(WATERSHED), y=abs.res.LLSC)) +
geom_boxplot()
A2.SBLL.F <- aov(abs.res.SBLL ~ WATERSHED, data=form3)
summary(A2.SBLL.F)## Df Sum Sq Mean Sq F value Pr(>F)
## WATERSHED 11 5.086 0.4623 4.741 4.93e-06 ***
## Residuals 122 11.897 0.0975
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1ggplot(form3, aes(x=factor(WATERSHED), y=abs.res.SBLL)) +
geom_boxplot()
A2.BD.F <- aov(abs.res.BD ~ WATERSHED, data=form3)
summary(A2.BD.F)## Df Sum Sq Mean Sq F value Pr(>F)
## WATERSHED 11 0.01278 0.001162 0.871 0.571
## Residuals 122 0.16271 0.001334ggplot(form3, aes(x=factor(WATERSHED), y=abs.res.BD)) +
geom_boxplot()
A2.CPD.F <- aov(abs.res.CPD ~ WATERSHED, data=form3)
summary(A2.CPD.F)## Df Sum Sq Mean Sq F value Pr(>F)
## WATERSHED 11 0.01833 0.0016662 2.77 0.00304 **
## Residuals 122 0.07338 0.0006015
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1ggplot(form3, aes(x=factor(WATERSHED), y=abs.res.CPD)) +
geom_boxplot()
A2.CPL.F <- aov(abs.res.CPL ~ WATERSHED, data=form3)
summary(A2.CPL.F)## Df Sum Sq Mean Sq F value Pr(>F)
## WATERSHED 11 0.03237 0.0029429 4.301 2.05e-05 ***
## Residuals 122 0.08347 0.0006842
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1A2.PreDL.F <- aov(abs.res.PreDL ~ WATERSHED, data=form3)
summary(A2.PreDL.F)## Df Sum Sq Mean Sq F value Pr(>F)
## WATERSHED 11 0.00568 0.0005163 1.191 0.3
## Residuals 122 0.05288 0.0004334A2.DbL.F <- aov(abs.res.DbL ~ WATERSHED, data=form3)
summary(A2.DbL.F)## Df Sum Sq Mean Sq F value Pr(>F)
## WATERSHED 11 0.04272 0.003883 2.351 0.0115 *
## Residuals 122 0.20152 0.001652
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1ggplot(form3, aes(x=factor(WATERSHED), y=abs.res.DbL)) +
geom_boxplot()
A2.HL.F <- aov(abs.res.HL ~ WATERSHED, data=form3)
summary(A2.HL.F)## Df Sum Sq Mean Sq F value Pr(>F)
## WATERSHED 11 0.01169 0.0010627 1.243 0.267
## Residuals 122 0.10435 0.0008553ggplot(form3, aes(x=factor(WATERSHED), y=abs.res.HL)) +
geom_boxplot()
A2.HD.F <- aov(abs.res.HD ~ WATERSHED, data=form3)
summary(A2.HD.F)## Df Sum Sq Mean Sq F value Pr(>F)
## WATERSHED 11 0.01036 0.0009418 0.826 0.614
## Residuals 122 0.13905 0.0011397ggplot(form3, aes(x=factor(WATERSHED), y=abs.res.HD)) +
geom_boxplot()
A2.HW.F <- aov(abs.res.HW ~ WATERSHED, data=form3)
summary(A2.HW.F)## Df Sum Sq Mean Sq F value Pr(>F)
## WATERSHED 11 0.01704 0.0015488 3.018 0.00136 **
## Residuals 122 0.06260 0.0005131
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1ggplot(form3, aes(x=factor(WATERSHED), y=abs.res.HW)) +
geom_boxplot()
A2.SnL.F <- aov(abs.res.SnL ~ WATERSHED, data=form3)
summary(A2.SnL.F)## Df Sum Sq Mean Sq F value Pr(>F)
## WATERSHED 11 0.02208 0.0020073 4.772 4.46e-06 ***
## Residuals 122 0.05131 0.0004206
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1A2.OL.F <- aov(abs.res.OL ~ WATERSHED, data=form3)
summary(A2.OL.F)## Df Sum Sq Mean Sq F value Pr(>F)
## WATERSHED 11 2.610e-32 2.372e-33 0.476 0.915
## Residuals 122 6.077e-31 4.981e-33ggplot(form3, aes(x=factor(WATERSHED), y=abs.res.OL)) +
geom_boxplot()
Sailfin
Zones
library(ggplot2)
A.D.L <- aov(abs.res.D ~ QUARTILE, data=lat3)
summary(A.D.L)## Df Sum Sq Mean Sq F value Pr(>F)
## QUARTILE 3 2.306 0.7685 4.292 0.00635 **
## Residuals 130 23.277 0.1791
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1ggplot(lat3, aes(x=factor(QUARTILE), y=abs.res.D)) +
geom_boxplot()
A.P1.L <- aov(abs.res.P1 ~ QUARTILE, data=lat3)
summary(A.P1.L)## Df Sum Sq Mean Sq F value Pr(>F)
## QUARTILE 3 0.159 0.05296 0.444 0.722
## Residuals 130 15.511 0.11932A.P1.R.L <- aov(abs.res.P1.R ~ QUARTILE, data=lat3)
summary(A.P1.R.L)## Df Sum Sq Mean Sq F value Pr(>F)
## QUARTILE 3 0.065 0.02172 0.166 0.919
## Residuals 130 16.987 0.13067ggplot(lat3, aes(x=factor(QUARTILE), y=abs.res.P1.R)) +
geom_boxplot()
A.LLSC.L <- aov(abs.res.LLSC ~ QUARTILE, data=lat3)
summary(A.LLSC.L)## Df Sum Sq Mean Sq F value Pr(>F)
## QUARTILE 3 1.31 0.4354 1.209 0.309
## Residuals 130 46.80 0.3600A.SBLL.L <- aov(abs.res.SBLL ~ QUARTILE, data=lat3)
summary(A.SBLL.L)## Df Sum Sq Mean Sq F value Pr(>F)
## QUARTILE 3 0.436 0.1454 1.142 0.335
## Residuals 130 16.546 0.1273ggplot(lat3, aes(x=factor(QUARTILE), y=abs.res.SBLL)) +
geom_boxplot()
A.BD.L <- aov(abs.res.BD ~ QUARTILE, data=lat3)
summary(A.BD.L)## Df Sum Sq Mean Sq F value Pr(>F)
## QUARTILE 3 0.00594 0.001981 1.519 0.213
## Residuals 130 0.16955 0.001304ggplot(lat3, aes(x=factor(QUARTILE), y=abs.res.BD)) +
geom_boxplot()
A.CPD.L <- aov(abs.res.CPD ~ QUARTILE, data=lat3)
summary(A.CPD.L)## Df Sum Sq Mean Sq F value Pr(>F)
## QUARTILE 3 0.01249 0.004163 6.832 0.00026 ***
## Residuals 130 0.07922 0.000609
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1ggplot(lat3, aes(x=factor(QUARTILE), y=abs.res.CPD)) +
geom_boxplot()
A.CPL.L <- aov(abs.res.CPL ~ QUARTILE, data=lat3)
summary(A.CPL.L)## Df Sum Sq Mean Sq F value Pr(>F)
## QUARTILE 3 0.02074 0.006912 9.448 1.08e-05 ***
## Residuals 130 0.09511 0.000732
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1ggplot(lat3, aes(x=factor(QUARTILE), y=abs.res.CPL)) +
geom_boxplot()
A.PreDL.L <- aov(abs.res.PreDL ~ QUARTILE, data=lat3)
summary(A.PreDL.L)## Df Sum Sq Mean Sq F value Pr(>F)
## QUARTILE 3 0.00209 0.0006977 1.606 0.191
## Residuals 130 0.05646 0.0004343ggplot(lat3, aes(x=factor(QUARTILE), y=abs.res.PreDL)) +
geom_boxplot()
A.DbL.L <- aov(abs.res.DbL ~ QUARTILE, data=lat3)
summary(A.DbL.L)## Df Sum Sq Mean Sq F value Pr(>F)
## QUARTILE 3 0.01219 0.004063 2.276 0.0828 .
## Residuals 130 0.23204 0.001785
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1ggplot(lat3, aes(x=factor(QUARTILE), y=abs.res.DbL)) +
geom_boxplot()
A.HL.L <- aov(abs.res.HL ~ QUARTILE, data=lat3)
summary(A.HL.L)## Df Sum Sq Mean Sq F value Pr(>F)
## QUARTILE 3 0.00344 0.0011466 1.324 0.269
## Residuals 130 0.11260 0.0008661ggplot(lat3, aes(x=factor(QUARTILE), y=abs.res.HL)) +
geom_boxplot()
A.HD.L <- aov(abs.res.HD ~ QUARTILE, data=lat3)
summary(A.HD.L)## Df Sum Sq Mean Sq F value Pr(>F)
## QUARTILE 3 0.00672 0.002239 2.04 0.111
## Residuals 130 0.14269 0.001098A.HW.L <- aov(abs.res.HW ~ QUARTILE, data=lat3)
summary(A.HW.L)## Df Sum Sq Mean Sq F value Pr(>F)
## QUARTILE 3 0.01136 0.003788 7.212 0.000163 ***
## Residuals 130 0.06827 0.000525
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1ggplot(lat3, aes(x=factor(QUARTILE), y=abs.res.HW)) +
geom_boxplot()
A.SnL.L <- aov(abs.res.SnL ~ QUARTILE, data=lat3)
summary(A.SnL.L)## Df Sum Sq Mean Sq F value Pr(>F)
## QUARTILE 3 0.00766 0.0025545 5.052 0.00242 **
## Residuals 130 0.06573 0.0005056
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1A.OL.L <- aov(abs.res.OL ~ QUARTILE, data=lat3)
summary(A.OL.L)## Df Sum Sq Mean Sq F value Pr(>F)
## QUARTILE 3 2.17e-32 7.242e-33 1.538 0.208
## Residuals 130 6.12e-31 4.708e-33ggplot(lat3, aes(x=factor(QUARTILE), y=abs.res.OL)) +
geom_boxplot()
Basins
A1.D.L <- aov(abs.res.D ~ BASIN, data=lat3)
summary(A1.D.L)## Df Sum Sq Mean Sq F value Pr(>F)
## BASIN 5 2.789 0.5579 3.133 0.0106 *
## Residuals 128 22.793 0.1781
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1ggplot(lat3, aes(x=factor(BASIN), y=abs.res.D)) +
geom_boxplot()
A1.P1.L <- aov(abs.res.P1 ~ BASIN, data=lat3)
summary(A1.P1.L)## Df Sum Sq Mean Sq F value Pr(>F)
## BASIN 5 0.945 0.1891 1.643 0.153
## Residuals 128 14.725 0.1150A1.P1.R.L <- aov(abs.res.P1.R ~ BASIN, data=lat3)
summary(A1.P1.R.L)## Df Sum Sq Mean Sq F value Pr(>F)
## BASIN 5 0.159 0.03187 0.241 0.943
## Residuals 128 16.893 0.13197ggplot(lat3, aes(x=factor(BASIN), y=abs.res.P1.R)) +
geom_boxplot()
A1.LLSC.L <- aov(abs.res.LLSC ~ BASIN, data=lat3)
summary(A1.LLSC.L)## Df Sum Sq Mean Sq F value Pr(>F)
## BASIN 5 4.54 0.9080 2.668 0.025 *
## Residuals 128 43.57 0.3404
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1ggplot(lat3, aes(x=factor(BASIN), y=abs.res.LLSC)) +
geom_boxplot()
A1.SBLL.L <- aov(abs.res.SBLL ~ BASIN, data=lat3)
summary(A1.SBLL.L)## Df Sum Sq Mean Sq F value Pr(>F)
## BASIN 5 0.755 0.1510 1.191 0.317
## Residuals 128 16.228 0.1268ggplot(lat3, aes(x=factor(BASIN), y=abs.res.SBLL)) +
geom_boxplot()
A1.BD.L <- aov(abs.res.BD ~ BASIN, data=lat3)
summary(A1.BD.L)## Df Sum Sq Mean Sq F value Pr(>F)
## BASIN 5 0.00786 0.001571 1.2 0.313
## Residuals 128 0.16764 0.001310ggplot(lat3, aes(x=factor(BASIN), y=abs.res.BD)) +
geom_boxplot()
A1.CPD.L <- aov(abs.res.CPD ~ BASIN, data=lat3)
summary(A1.CPD.L)## Df Sum Sq Mean Sq F value Pr(>F)
## BASIN 5 0.01713 0.003425 5.879 6.34e-05 ***
## Residuals 128 0.07458 0.000583
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1ggplot(lat3, aes(x=factor(BASIN), y=abs.res.CPD)) +
geom_boxplot()
A1.CPL.L <- aov(abs.res.CPL ~ BASIN, data=lat3)
summary(A1.CPL.L)## Df Sum Sq Mean Sq F value Pr(>F)
## BASIN 5 0.02013 0.004025 5.383 0.000159 ***
## Residuals 128 0.09572 0.000748
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1A1.PreDL.L <- aov(abs.res.PreDL ~ BASIN, data=lat3)
summary(A1.PreDL.L)## Df Sum Sq Mean Sq F value Pr(>F)
## BASIN 5 0.00492 0.0009846 2.35 0.0445 *
## Residuals 128 0.05363 0.0004190
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1ggplot(lat3, aes(x=factor(BASIN), y=abs.res.PreDL)) +
geom_boxplot()
A1.DbL.L <- aov(abs.res.DbL ~ BASIN, data=lat3)
summary(A1.DbL.L)## Df Sum Sq Mean Sq F value Pr(>F)
## BASIN 5 0.00996 0.001992 1.088 0.37
## Residuals 128 0.23428 0.001830ggplot(lat3, aes(x=factor(BASIN), y=abs.res.DbL)) +
geom_boxplot()
A1.HL.L <- aov(abs.res.HL ~ BASIN, data=lat3)
summary(A1.HL.L)## Df Sum Sq Mean Sq F value Pr(>F)
## BASIN 5 0.00766 0.0015321 1.809 0.115
## Residuals 128 0.10838 0.0008467ggplot(lat3, aes(x=factor(BASIN), y=abs.res.HL)) +
geom_boxplot()
A1.HD.L <- aov(abs.res.HD ~ BASIN, data=lat3)
summary(A1.HD.L)## Df Sum Sq Mean Sq F value Pr(>F)
## BASIN 5 0.00684 0.001367 1.228 0.3
## Residuals 128 0.14257 0.001114ggplot(lat3, aes(x=factor(BASIN), y=abs.res.HD)) +
geom_boxplot()
A1.HW.L <- aov(abs.res.HW ~ BASIN, data=lat3)
summary(A1.HW.L)## Df Sum Sq Mean Sq F value Pr(>F)
## BASIN 5 0.01460 0.0029194 5.746 8.11e-05 ***
## Residuals 128 0.06504 0.0005081
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1ggplot(lat3, aes(x=factor(BASIN), y=abs.res.HW)) +
geom_boxplot()
A1.SnL.L <- aov(abs.res.SnL ~ BASIN, data=lat3)
summary(A1.SnL.L)## Df Sum Sq Mean Sq F value Pr(>F)
## BASIN 5 0.01931 0.003861 9.138 1.87e-07 ***
## Residuals 128 0.05409 0.000423
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1A1.OL.L <- aov(abs.res.OL ~ BASIN, data=lat3)
summary(A1.OL.L)## Df Sum Sq Mean Sq F value Pr(>F)
## BASIN 5 1.240e-32 2.479e-33 0.511 0.768
## Residuals 128 6.214e-31 4.854e-33ggplot(lat3, aes(x=factor(BASIN), y=abs.res.OL)) +
geom_boxplot()
Watersheds
A2.D.L <- aov(abs.res.D ~ WATERSHED, data=lat3)
summary(A2.D.L)## Df Sum Sq Mean Sq F value Pr(>F)
## WATERSHED 11 3.847 0.3497 1.963 0.0378 *
## Residuals 122 21.736 0.1782
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1ggplot(lat3, aes(x=factor(WATERSHED), y=abs.res.D)) +
geom_boxplot()
A2.P1.L <- aov(abs.res.P1 ~ WATERSHED, data=lat3)
summary(A2.P1.L)## Df Sum Sq Mean Sq F value Pr(>F)
## WATERSHED 11 1.302 0.1184 1.005 0.446
## Residuals 122 14.368 0.1178A2.P1.R.L <- aov(abs.res.P1.R ~ WATERSHED, data=lat3)
summary(A2.P1.R.L)## Df Sum Sq Mean Sq F value Pr(>F)
## WATERSHED 11 0.34 0.03093 0.226 0.995
## Residuals 122 16.71 0.13698ggplot(lat3, aes(x=factor(WATERSHED), y=abs.res.P1.R)) +
geom_boxplot()
A2.LLSC.L <- aov(abs.res.LLSC ~ WATERSHED, data=lat3)
summary(A2.LLSC.L)## Df Sum Sq Mean Sq F value Pr(>F)
## WATERSHED 11 8.16 0.7422 2.267 0.015 *
## Residuals 122 39.94 0.3274
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1ggplot(lat3, aes(x=factor(WATERSHED), y=abs.res.LLSC)) +
geom_boxplot()
A2.SBLL.L <- aov(abs.res.SBLL ~ WATERSHED, data=lat3)
summary(A2.SBLL.L)## Df Sum Sq Mean Sq F value Pr(>F)
## WATERSHED 11 5.086 0.4623 4.741 4.93e-06 ***
## Residuals 122 11.897 0.0975
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1ggplot(lat3, aes(x=factor(WATERSHED), y=abs.res.SBLL)) +
geom_boxplot()
A2.BD.L <- aov(abs.res.BD ~ WATERSHED, data=lat3)
summary(A2.BD.L)## Df Sum Sq Mean Sq F value Pr(>F)
## WATERSHED 11 0.01278 0.001162 0.871 0.571
## Residuals 122 0.16271 0.001334ggplot(lat3, aes(x=factor(WATERSHED), y=abs.res.BD)) +
geom_boxplot()
A2.CPD.L <- aov(abs.res.CPD ~ WATERSHED, data=lat3)
summary(A2.CPD.L)## Df Sum Sq Mean Sq F value Pr(>F)
## WATERSHED 11 0.01833 0.0016662 2.77 0.00304 **
## Residuals 122 0.07338 0.0006015
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1ggplot(lat3, aes(x=factor(WATERSHED), y=abs.res.CPD)) +
geom_boxplot()
A2.CPL.L <- aov(abs.res.CPL ~ WATERSHED, data=lat3)
summary(A2.CPL.L)## Df Sum Sq Mean Sq F value Pr(>F)
## WATERSHED 11 0.03237 0.0029429 4.301 2.05e-05 ***
## Residuals 122 0.08347 0.0006842
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1A2.PreDL.L <- aov(abs.res.PreDL ~ WATERSHED, data=lat3)
summary(A2.PreDL.L)## Df Sum Sq Mean Sq F value Pr(>F)
## WATERSHED 11 0.00568 0.0005163 1.191 0.3
## Residuals 122 0.05288 0.0004334A2.DbL.L <- aov(abs.res.DbL ~ WATERSHED, data=lat3)
summary(A2.DbL.L)## Df Sum Sq Mean Sq F value Pr(>F)
## WATERSHED 11 0.04272 0.003883 2.351 0.0115 *
## Residuals 122 0.20152 0.001652
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1ggplot(lat3, aes(x=factor(WATERSHED), y=abs.res.DbL)) +
geom_boxplot()
A2.HL.L <- aov(abs.res.HL ~ WATERSHED, data=lat3)
summary(A2.HL.L)## Df Sum Sq Mean Sq F value Pr(>F)
## WATERSHED 11 0.01169 0.0010627 1.243 0.267
## Residuals 122 0.10435 0.0008553ggplot(lat3, aes(x=factor(WATERSHED), y=abs.res.HL)) +
geom_boxplot()
A2.HD.L <- aov(abs.res.HD ~ WATERSHED, data=lat3)
summary(A2.HD.L)## Df Sum Sq Mean Sq F value Pr(>F)
## WATERSHED 11 0.01036 0.0009418 0.826 0.614
## Residuals 122 0.13905 0.0011397ggplot(lat3, aes(x=factor(WATERSHED), y=abs.res.HD)) +
geom_boxplot()
A2.HW.L <- aov(abs.res.HW ~ WATERSHED, data=lat3)
summary(A2.HW.L)## Df Sum Sq Mean Sq F value Pr(>F)
## WATERSHED 11 0.01704 0.0015488 3.018 0.00136 **
## Residuals 122 0.06260 0.0005131
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1ggplot(lat3, aes(x=factor(WATERSHED), y=abs.res.HW)) +
geom_boxplot()
A2.SnL.L <- aov(abs.res.SnL ~ WATERSHED, data=lat3)
summary(A2.SnL.L)## Df Sum Sq Mean Sq F value Pr(>F)
## WATERSHED 11 0.02208 0.0020073 4.772 4.46e-06 ***
## Residuals 122 0.05131 0.0004206
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1A2.OL.L <- aov(abs.res.OL ~ WATERSHED, data=lat3)
summary(A2.OL.L)## Df Sum Sq Mean Sq F value Pr(>F)
## WATERSHED 11 2.610e-32 2.372e-33 0.476 0.915
## Residuals 122 6.077e-31 4.981e-33ggplot(lat3, aes(x=factor(WATERSHED), y=abs.res.OL)) +
geom_boxplot()
Both
Zones
library(ggplot2)
A.D <- aov(abs.res.D ~ SPP*QUARTILE, data=raw3)
summary(A.D)## Df Sum Sq Mean Sq F value Pr(>F)
## SPP 1 0.06 0.0635 0.408 0.52344
## QUARTILE 3 0.45 0.1510 0.970 0.40715
## SPP:QUARTILE 3 3.22 1.0719 6.888 0.00017 ***
## Residuals 292 45.44 0.1556
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1ggplot(raw3, aes(x=factor(QUARTILE), y=abs.res.D, fill=SPP)) +
geom_boxplot()
A.P1.L <- aov(abs.res.P1 ~ SPP*QUARTILE, data=raw3)
summary(A.P1.L)## Df Sum Sq Mean Sq F value Pr(>F)
## SPP 1 0.29 0.2878 1.554 0.214
## QUARTILE 3 1.10 0.3663 1.977 0.117
## SPP:QUARTILE 3 0.73 0.2427 1.310 0.271
## Residuals 292 54.10 0.1853A.P1.R <- aov(abs.res.P1.R ~ SPP*QUARTILE, data=raw3)
summary(A.P1.R)## Df Sum Sq Mean Sq F value Pr(>F)
## SPP 1 1.80 1.7983 11.423 0.000824 ***
## QUARTILE 3 0.13 0.0434 0.276 0.842918
## SPP:QUARTILE 3 0.06 0.0189 0.120 0.948162
## Residuals 292 45.97 0.1574
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1ggplot(raw3, aes(x=factor(QUARTILE), y=abs.res.P1.R, fill=SPP)) +
geom_boxplot()
A.LLSC <- aov(abs.res.LLSC ~ SPP*QUARTILE, data=raw3)
summary(A.LLSC)## Df Sum Sq Mean Sq F value Pr(>F)
## SPP 1 1.40 1.4013 2.940 0.0875 .
## QUARTILE 3 1.35 0.4506 0.945 0.4190
## SPP:QUARTILE 3 3.42 1.1399 2.391 0.0688 .
## Residuals 292 139.19 0.4767
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1A.SBLL <- aov(abs.res.SBLL ~ SPP*QUARTILE, data=raw3)
summary(A.SBLL)## Df Sum Sq Mean Sq F value Pr(>F)
## SPP 1 0.65 0.6523 4.859 0.0283 *
## QUARTILE 3 0.78 0.2591 1.930 0.1248
## SPP:QUARTILE 3 0.12 0.0390 0.291 0.8320
## Residuals 292 39.20 0.1342
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1ggplot(raw3, aes(x=factor(QUARTILE), y=abs.res.SBLL, fill=SPP)) +
geom_boxplot()
A.BD <- aov(abs.res.BD ~ SPP*QUARTILE, data=raw3)
summary(A.BD)## Df Sum Sq Mean Sq F value Pr(>F)
## SPP 1 0.0000 0.0000346 0.026 0.8726
## QUARTILE 3 0.0015 0.0004855 0.361 0.7811
## SPP:QUARTILE 3 0.0087 0.0028846 2.146 0.0946 .
## Residuals 292 0.3925 0.0013442
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1ggplot(raw3, aes(x=factor(QUARTILE), y=abs.res.BD, fill=SPP)) +
geom_boxplot()
A.CPD <- aov(abs.res.CPD ~ SPP*QUARTILE, data=raw3)
summary(A.CPD)## Df Sum Sq Mean Sq F value Pr(>F)
## SPP 1 0.00312 0.0031247 4.900 0.02764 *
## QUARTILE 3 0.00786 0.0026201 4.108 0.00707 **
## SPP:QUARTILE 3 0.00713 0.0023775 3.728 0.01176 *
## Residuals 292 0.18622 0.0006377
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1ggplot(raw3, aes(x=factor(QUARTILE), y=abs.res.CPD, fill=SPP)) +
geom_boxplot()
A.CPL <- aov(abs.res.CPL ~ SPP*QUARTILE, data=raw3)
summary(A.CPL)## Df Sum Sq Mean Sq F value Pr(>F)
## SPP 1 0.00000 0.000000 0.000 0.986836
## QUARTILE 3 0.01640 0.005468 6.588 0.000254 ***
## SPP:QUARTILE 3 0.02033 0.006777 8.166 3.08e-05 ***
## Residuals 292 0.24236 0.000830
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1ggplot(raw3, aes(x=factor(QUARTILE), y=abs.res.CPL, fill=SPP)) +
geom_boxplot()
A.PreDL <- aov(abs.res.PreDL ~ SPP*QUARTILE, data=raw3)
summary(A.PreDL)## Df Sum Sq Mean Sq F value Pr(>F)
## SPP 1 0.00006 0.0000590 0.145 0.7035
## QUARTILE 3 0.00243 0.0008091 1.991 0.1155
## SPP:QUARTILE 3 0.00392 0.0013082 3.218 0.0232 *
## Residuals 292 0.11869 0.0004065
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1ggplot(raw3, aes(x=factor(QUARTILE), y=abs.res.PreDL, fill=SPP)) +
geom_boxplot()
A.DbL <- aov(abs.res.DbL ~ SPP*QUARTILE, data=raw3)
summary(A.DbL)## Df Sum Sq Mean Sq F value Pr(>F)
## SPP 1 0.0001 0.000068 0.037 0.847
## QUARTILE 3 0.0060 0.001997 1.093 0.352
## SPP:QUARTILE 3 0.0068 0.002277 1.246 0.293
## Residuals 292 0.5335 0.001827ggplot(raw3, aes(x=factor(QUARTILE), y=abs.res.DbL, fill=SPP)) +
geom_boxplot()
A.HL <- aov(abs.res.HL ~ SPP*QUARTILE, data=raw3)
summary(A.HL)## Df Sum Sq Mean Sq F value Pr(>F)
## SPP 1 0.00081 0.000812 0.861 0.3541
## QUARTILE 3 0.02099 0.006995 7.421 8.33e-05 ***
## SPP:QUARTILE 3 0.01029 0.003432 3.640 0.0132 *
## Residuals 292 0.27527 0.000943
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1ggplot(raw3, aes(x=factor(QUARTILE), y=abs.res.HL, fill=SPP)) +
geom_boxplot()
A.HD <- aov(abs.res.HD ~ SPP*QUARTILE, data=raw3)
summary(A.HD)## Df Sum Sq Mean Sq F value Pr(>F)
## SPP 1 0.00000 0.0000000 0.000 0.999
## QUARTILE 3 0.00443 0.0014757 1.522 0.209
## SPP:QUARTILE 3 0.00582 0.0019390 1.999 0.114
## Residuals 292 0.28319 0.0009698A.HW <- aov(abs.res.HW ~ SPP*QUARTILE, data=raw3)
summary(A.HW)## Df Sum Sq Mean Sq F value Pr(>F)
## SPP 1 0.00213 0.0021307 2.861 0.09184 .
## QUARTILE 3 0.00917 0.0030561 4.103 0.00712 **
## SPP:QUARTILE 3 0.00710 0.0023664 3.177 0.02448 *
## Residuals 292 0.21750 0.0007449
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1ggplot(raw3, aes(x=factor(QUARTILE), y=abs.res.HW, fill=SPP)) +
geom_boxplot()
A.SnL <- aov(abs.res.SnL ~ SPP*QUARTILE, data=raw3)
summary(A.SnL)## Df Sum Sq Mean Sq F value Pr(>F)
## SPP 1 0.00009 0.000095 0.163 0.6867
## QUARTILE 3 0.01743 0.005809 9.995 2.73e-06 ***
## SPP:QUARTILE 3 0.00494 0.001647 2.833 0.0386 *
## Residuals 292 0.16972 0.000581
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1A.OL <- aov(abs.res.OL ~ SPP*QUARTILE, data=raw3)
summary(A.OL)## Df Sum Sq Mean Sq F value Pr(>F)
## SPP 1 4.900e-33 4.915e-33 2.108 0.1476
## QUARTILE 3 1.830e-32 6.103e-33 2.617 0.0512 .
## SPP:QUARTILE 3 5.800e-33 1.948e-33 0.835 0.4754
## Residuals 292 6.809e-31 2.332e-33
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1ggplot(raw3, aes(x=factor(QUARTILE), y=abs.res.OL, fill=SPP)) +
geom_boxplot()
Basins
A1.D <- aov(abs.res.D ~ SPP*BASIN, data=raw3)
summary(A1.D)## Df Sum Sq Mean Sq F value Pr(>F)
## SPP 1 0.06 0.0635 0.402 0.52666
## BASIN 6 3.12 0.5205 3.293 0.00377 **
## SPP:BASIN 3 0.31 0.1028 0.650 0.58344
## Residuals 289 45.68 0.1581
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1ggplot(raw3, aes(x=factor(BASIN), y=abs.res.D, fill=SPP)) +
geom_boxplot()
A1.P1 <- aov(abs.res.P1 ~ SPP*BASIN, data=raw3)
summary(A1.P1)## Df Sum Sq Mean Sq F value Pr(>F)
## SPP 1 0.29 0.2878 1.528 0.217
## BASIN 6 0.97 0.1613 0.856 0.528
## SPP:BASIN 3 0.53 0.1751 0.930 0.427
## Residuals 289 54.43 0.1883A1.P1.R <- aov(abs.res.P1.R ~ SPP*BASIN, data=raw3)
summary(A1.P1.R)## Df Sum Sq Mean Sq F value Pr(>F)
## SPP 1 1.80 1.7983 11.421 0.000826 ***
## BASIN 6 0.51 0.0845 0.537 0.780341
## SPP:BASIN 3 0.15 0.0485 0.308 0.819718
## Residuals 289 45.50 0.1575
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1ggplot(raw3, aes(x=factor(BASIN), y=abs.res.P1.R, fill=SPP)) +
geom_boxplot()
A1.LLSC <- aov(abs.res.LLSC ~ SPP*BASIN, data=raw3)
summary(A1.LLSC)## Df Sum Sq Mean Sq F value Pr(>F)
## SPP 1 1.40 1.4013 2.999 0.0844 .
## BASIN 6 6.83 1.1376 2.435 0.0260 *
## SPP:BASIN 3 2.11 0.7026 1.504 0.2137
## Residuals 289 135.02 0.4672
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1ggplot(raw3, aes(x=factor(BASIN), y=abs.res.LLSC, fill=SPP)) +
geom_boxplot()
A1.SBLL <- aov(abs.res.SBLL ~ SPP*BASIN, data=raw3)
summary(A1.SBLL)## Df Sum Sq Mean Sq F value Pr(>F)
## SPP 1 0.65 0.6523 4.895 0.0277 *
## BASIN 6 1.07 0.1785 1.340 0.2393
## SPP:BASIN 3 0.51 0.1716 1.288 0.2788
## Residuals 289 38.51 0.1332
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1ggplot(raw3, aes(x=factor(BASIN), y=abs.res.SBLL, fill=SPP)) +
geom_boxplot()
A1.BD <- aov(abs.res.BD ~ SPP*BASIN, data=raw3)
summary(A1.BD)## Df Sum Sq Mean Sq F value Pr(>F)
## SPP 1 0.0000 0.000035 0.027 0.8701
## BASIN 6 0.0190 0.003167 2.450 0.0251 *
## SPP:BASIN 3 0.0101 0.003367 2.605 0.0520 .
## Residuals 289 0.3735 0.001292
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1ggplot(raw3, aes(x=factor(BASIN), y=abs.res.BD, fill=SPP)) +
geom_boxplot()
A1.CPD <- aov(abs.res.CPD ~ SPP*BASIN, data=raw3)
summary(A1.CPD)## Df Sum Sq Mean Sq F value Pr(>F)
## SPP 1 0.00312 0.0031247 4.984 0.026343 *
## BASIN 6 0.01576 0.0026273 4.191 0.000464 ***
## SPP:BASIN 3 0.00428 0.0014261 2.275 0.080070 .
## Residuals 289 0.18117 0.0006269
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1ggplot(raw3, aes(x=factor(BASIN), y=abs.res.CPD, fill=SPP)) +
geom_boxplot()
A1.CPL <- aov(abs.res.CPL ~ SPP*BASIN, data=raw3)
summary(A1.CPL)## Df Sum Sq Mean Sq F value Pr(>F)
## SPP 1 0.00000 0.000000 0.000 0.987
## BASIN 6 0.03228 0.005380 6.320 2.92e-06 ***
## SPP:BASIN 3 0.00078 0.000259 0.304 0.822
## Residuals 289 0.24603 0.000851
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1A1.PreDL <- aov(abs.res.PreDL ~ SPP*BASIN, data=raw3)
summary(A1.PreDL)## Df Sum Sq Mean Sq F value Pr(>F)
## SPP 1 0.00006 0.0000590 0.147 0.7020
## BASIN 6 0.00466 0.0007773 1.932 0.0755 .
## SPP:BASIN 3 0.00412 0.0013741 3.416 0.0178 *
## Residuals 289 0.11626 0.0004023
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1ggplot(raw3, aes(x=factor(BASIN), y=abs.res.PreDL, fill=SPP)) +
geom_boxplot()
A1.DbL <- aov(abs.res.DbL ~ SPP*BASIN, data=raw3)
summary(A1.DbL)## Df Sum Sq Mean Sq F value Pr(>F)
## SPP 1 0.0001 0.000068 0.037 0.847
## BASIN 6 0.0152 0.002539 1.397 0.216
## SPP:BASIN 3 0.0057 0.001914 1.053 0.370
## Residuals 289 0.5254 0.001818ggplot(raw3, aes(x=factor(BASIN), y=abs.res.DbL, fill=SPP)) +
geom_boxplot()
A1.HL <- aov(abs.res.HL ~ SPP*BASIN, data=raw3)
summary(A1.HL)## Df Sum Sq Mean Sq F value Pr(>F)
## SPP 1 0.00081 0.000812 0.827 0.36379
## BASIN 6 0.02039 0.003398 3.463 0.00255 **
## SPP:BASIN 3 0.00256 0.000852 0.868 0.45782
## Residuals 289 0.28360 0.000981
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1ggplot(raw3, aes(x=factor(BASIN), y=abs.res.HL, fill=SPP)) +
geom_boxplot()
A1.HD <- aov(abs.res.HD ~ SPP*BASIN, data=raw3)
summary(A1.HD)## Df Sum Sq Mean Sq F value Pr(>F)
## SPP 1 0.00000 0.0000000 0.000 0.999
## BASIN 6 0.00478 0.0007959 0.808 0.565
## SPP:BASIN 3 0.00382 0.0012743 1.293 0.277
## Residuals 289 0.28484 0.0009856ggplot(raw3, aes(x=factor(BASIN), y=abs.res.HD, fill=SPP)) +
geom_boxplot()
A1.HW <- aov(abs.res.HW ~ SPP*BASIN, data=raw3)
summary(A1.HW)## Df Sum Sq Mean Sq F value Pr(>F)
## SPP 1 0.00213 0.0021307 2.825 0.09387 .
## BASIN 6 0.01505 0.0025085 3.326 0.00349 **
## SPP:BASIN 3 0.00076 0.0002544 0.337 0.79838
## Residuals 289 0.21795 0.0007542
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1ggplot(raw3, aes(x=factor(BASIN), y=abs.res.HW, fill=SPP)) +
geom_boxplot()
A1.SnL <- aov(abs.res.SnL ~ SPP*BASIN, data=raw3)
summary(A1.SnL)## Df Sum Sq Mean Sq F value Pr(>F)
## SPP 1 0.00009 0.000095 0.162 0.688
## BASIN 6 0.02054 0.003424 5.849 8.99e-06 ***
## SPP:BASIN 3 0.00238 0.000794 1.357 0.256
## Residuals 289 0.16916 0.000585
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1A1.OL <- aov(abs.res.OL ~ SPP*BASIN, data=raw3)
summary(A1.OL)## Df Sum Sq Mean Sq F value Pr(>F)
## SPP 1 4.900e-33 4.915e-33 2.054 0.153
## BASIN 6 9.200e-33 1.535e-33 0.641 0.697
## SPP:BASIN 3 4.100e-33 1.358e-33 0.567 0.637
## Residuals 289 6.917e-31 2.394e-33ggplot(raw3, aes(x=factor(BASIN), y=abs.res.OL, fill=SPP)) +
geom_boxplot()
Watersheds
A2.D <- aov(abs.res.D ~ SPP*WATERSHED, data=raw3)
summary(A2.D)## Df Sum Sq Mean Sq F value Pr(>F)
## SPP 1 0.06 0.0635 0.415 0.5198
## WATERSHED 13 4.33 0.3331 2.178 0.0106 *
## SPP:WATERSHED 5 1.96 0.3922 2.564 0.0274 *
## Residuals 280 42.82 0.1529
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1ggplot(raw3, aes(x=factor(WATERSHED), y=abs.res.D, fill=SPP)) +
geom_boxplot()
A2.P1 <- aov(abs.res.P1 ~ SPP*WATERSHED, data=raw3)
summary(A2.P1)## Df Sum Sq Mean Sq F value Pr(>F)
## SPP 1 0.29 0.2878 1.568 0.2116
## WATERSHED 13 3.73 0.2868 1.562 0.0957 .
## SPP:WATERSHED 5 0.78 0.1569 0.855 0.5120
## Residuals 280 51.41 0.1836
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1A2.P1.R <- aov(abs.res.P1.R ~ SPP*WATERSHED, data=raw3)
summary(A2.P1.R)## Df Sum Sq Mean Sq F value Pr(>F)
## SPP 1 1.80 1.7983 11.145 0.000957 ***
## WATERSHED 13 0.82 0.0629 0.390 0.972416
## SPP:WATERSHED 5 0.16 0.0322 0.199 0.962521
## Residuals 280 45.18 0.1614
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1ggplot(raw3, aes(x=factor(WATERSHED), y=abs.res.P1.R, fill=SPP)) +
geom_boxplot()
A2.LLSC <- aov(abs.res.LLSC ~ SPP*WATERSHED, data=raw3)
summary(A2.LLSC)## Df Sum Sq Mean Sq F value Pr(>F)
## SPP 1 1.40 1.4013 3.299 0.0704 .
## WATERSHED 13 20.28 1.5596 3.672 2.15e-05 ***
## SPP:WATERSHED 5 4.75 0.9502 2.237 0.0509 .
## Residuals 280 118.93 0.4248
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1ggplot(raw3, aes(x=factor(WATERSHED), y=abs.res.LLSC, fill=SPP)) +
geom_boxplot()
A2.SBLL <- aov(abs.res.SBLL ~ SPP*WATERSHED, data=raw3)
summary(A2.SBLL)## Df Sum Sq Mean Sq F value Pr(>F)
## SPP 1 0.65 0.6523 5.611 0.0185 *
## WATERSHED 13 2.98 0.2289 1.969 0.0233 *
## SPP:WATERSHED 5 4.57 0.9138 7.861 6.06e-07 ***
## Residuals 280 32.55 0.1162
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1ggplot(raw3, aes(x=factor(WATERSHED), y=abs.res.SBLL, fill=SPP)) +
geom_boxplot()
A2.BD <- aov(abs.res.BD ~ SPP*WATERSHED, data=raw3)
summary(A2.BD)## Df Sum Sq Mean Sq F value Pr(>F)
## SPP 1 0.0000 0.000035 0.028 0.86766
## WATERSHED 13 0.0427 0.003283 2.639 0.00171 **
## SPP:WATERSHED 5 0.0115 0.002309 1.856 0.10214
## Residuals 280 0.3484 0.001244
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1ggplot(raw3, aes(x=factor(WATERSHED), y=abs.res.BD, fill=SPP)) +
geom_boxplot()
A2.CPD <- aov(abs.res.CPD ~ SPP*WATERSHED, data=raw3)
summary(A2.CPD)## Df Sum Sq Mean Sq F value Pr(>F)
## SPP 1 0.00312 0.0031247 4.943 0.0270 *
## WATERSHED 13 0.01690 0.0012999 2.056 0.0169 *
## SPP:WATERSHED 5 0.00731 0.0014624 2.313 0.0441 *
## Residuals 280 0.17700 0.0006322
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1ggplot(raw3, aes(x=factor(WATERSHED), y=abs.res.CPD, fill=SPP)) +
geom_boxplot()
A2.CPL <- aov(abs.res.CPL ~ SPP*WATERSHED, data=raw3)
summary(A2.CPL)## Df Sum Sq Mean Sq F value Pr(>F)
## SPP 1 0.00000 0.000000 0.000 0.9866
## WATERSHED 13 0.04566 0.003512 4.406 8.64e-07 ***
## SPP:WATERSHED 5 0.01021 0.002043 2.563 0.0275 *
## Residuals 280 0.22322 0.000797
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1A2.PreDL <- aov(abs.res.PreDL ~ SPP*WATERSHED, data=raw3)
summary(A2.PreDL)## Df Sum Sq Mean Sq F value Pr(>F)
## SPP 1 0.00006 0.0000590 0.146 0.7022
## WATERSHED 13 0.00996 0.0007664 1.902 0.0297 *
## SPP:WATERSHED 5 0.00229 0.0004575 1.136 0.3416
## Residuals 280 0.11279 0.0004028
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1A2.DbL <- aov(abs.res.DbL ~ SPP*WATERSHED, data=raw3)
summary(A2.DbL)## Df Sum Sq Mean Sq F value Pr(>F)
## SPP 1 0.0001 0.000068 0.040 0.841516
## WATERSHED 13 0.0348 0.002680 1.579 0.090441 .
## SPP:WATERSHED 5 0.0363 0.007253 4.273 0.000923 ***
## Residuals 280 0.4752 0.001697
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1ggplot(raw3, aes(x=factor(WATERSHED), y=abs.res.DbL, fill=SPP)) +
geom_boxplot()
A2.HL <- aov(abs.res.HL ~ SPP*WATERSHED, data=raw3)
summary(A2.HL)## Df Sum Sq Mean Sq F value Pr(>F)
## SPP 1 0.00081 0.000812 0.896 0.345
## WATERSHED 13 0.05036 0.003874 4.275 1.54e-06 ***
## SPP:WATERSHED 5 0.00247 0.000494 0.546 0.742
## Residuals 280 0.25372 0.000906
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1ggplot(raw3, aes(x=factor(WATERSHED), y=abs.res.HL, fill=SPP)) +
geom_boxplot()
A2.HD <- aov(abs.res.HD ~ SPP*WATERSHED, data=raw3)
summary(A2.HD)## Df Sum Sq Mean Sq F value Pr(>F)
## SPP 1 0.00000 0.0000000 0.000 0.999
## WATERSHED 13 0.01725 0.0013271 1.371 0.173
## SPP:WATERSHED 5 0.00519 0.0010375 1.072 0.376
## Residuals 280 0.27100 0.0009678ggplot(raw3, aes(x=factor(WATERSHED), y=abs.res.HD, fill=SPP)) +
geom_boxplot()
A2.HW <- aov(abs.res.HW ~ SPP*WATERSHED, data=raw3)
summary(A2.HW)## Df Sum Sq Mean Sq F value Pr(>F)
## SPP 1 0.00213 0.0021307 2.862 0.0918 .
## WATERSHED 13 0.02008 0.0015446 2.075 0.0157 *
## SPP:WATERSHED 5 0.00521 0.0010418 1.399 0.2246
## Residuals 280 0.20848 0.0007446
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1ggplot(raw3, aes(x=factor(WATERSHED), y=abs.res.HW, fill=SPP)) +
geom_boxplot()
A2.SnL <- aov(abs.res.SnL ~ SPP*WATERSHED, data=raw3)
summary(A2.SnL)## Df Sum Sq Mean Sq F value Pr(>F)
## SPP 1 0.00009 0.0000948 0.180 0.672
## WATERSHED 13 0.04027 0.0030976 5.890 1.23e-09 ***
## SPP:WATERSHED 5 0.00457 0.0009144 1.739 0.126
## Residuals 280 0.14725 0.0005259
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1A2.OL <- aov(abs.res.OL ~ SPP*WATERSHED, data=raw3)
summary(A2.OL)## Df Sum Sq Mean Sq F value Pr(>F)
## SPP 1 4.900e-33 4.915e-33 2.037 0.155
## WATERSHED 13 2.900e-32 2.231e-33 0.925 0.528
## SPP:WATERSHED 5 2.000e-34 4.600e-35 0.019 1.000
## Residuals 280 6.758e-31 2.414e-33ggplot(raw3, aes(x=factor(WATERSHED), y=abs.res.OL, fill=SPP)) +
geom_boxplot()
Standardized
DON’T KNOW IF THIS IS USEFUL
The ANOVAs above focus on differences of particular traits as a factor of species and location. If we want to get an idea of variation in general as a factor of species and location, we can standardize the residuals (essentially unitless z-scores of residuals).
sd.res.D <- append(abs(sd.lat.D), abs(sd.form.D))
sd.res.P1 <- append(abs(sd.lat.P1), abs(sd.form.P1))
sd.res.P1.R <- append(abs(sd.lat.P1.R), abs(sd.form.P1.R))
sd.res.LLSC<- append(abs(sd.lat.LLSC), abs(sd.form.LLSC))
sd.res.SBLL<- append(abs(sd.lat.SBLL), abs(sd.form.SBLL))
sd.res.BD<- append(abs(sd.lat.BD), abs(sd.form.BD))
sd.res.CPD<- append(abs(sd.lat.CPD), abs(sd.form.CPD))
sd.res.CPL<- append(abs(sd.lat.CPL), abs(sd.form.CPL))
sd.res.PreDL <- append(abs(sd.lat.PreDL), abs(sd.form.PreDL))
sd.res.DbL <- append(abs(sd.lat.DbL), abs(sd.form.DbL))
sd.res.HL<- append(abs(sd.lat.HL), abs(sd.form.HL))
sd.res.HD<- append(abs(sd.lat.HD), abs(sd.form.HD))
sd.res.HW <- append(abs(sd.lat.HW), abs(sd.form.HW))
sd.res.SnL <- append(abs(sd.lat.SnL), abs(sd.form.SnL))
sd.res.OL <- append(abs(sd.lat.OL), abs(sd.form.OL))
raw4 <- cbind(raw3, sd.res.D, sd.res.P1, sd.res.P1.R, sd.res.LLSC, sd.res.SBLL, sd.res.BD, sd.res.CPD, sd.res.CPL, sd.res.PreDL, sd.res.DbL, sd.res.HL, sd.res.HD, sd.res.HW, sd.res.SnL, sd.res.OL)
raw5 <- cbind(raw4[1:14], stack(raw4[53:68])) ## Warning in data.frame(..., check.names = FALSE): row names were found from a
## short variable and have been discardedlat.raw5 <- raw5[raw5$SPP == "p.latipinna",]
form.raw5 <- raw5[raw5$SPP == "p.formosa",]
######ZONES#####
A3.lat <- aov(values~QUARTILE, data=lat.raw5)
summary(A3.lat)## Df Sum Sq Mean Sq F value Pr(>F)
## QUARTILE 3 0.6 0.2106 1.13 0.336
## Residuals 2140 398.9 0.1864A3.form <- aov(values~QUARTILE, data=form.raw5)
summary(A3.form)## Df Sum Sq Mean Sq F value Pr(>F)
## QUARTILE 3 1.9 0.6213 2.851 0.0361 *
## Residuals 2652 578.0 0.2180
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1#between species
A3 <- aov(values~QUARTILE*SPP, data=raw5)
summary(A3)## Df Sum Sq Mean Sq F value Pr(>F)
## QUARTILE 3 0.8 0.2626 1.288 0.277
## SPP 1 0.1 0.0604 0.296 0.586
## QUARTILE:SPP 3 1.7 0.5578 2.736 0.042 *
## Residuals 4792 976.9 0.2039
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1ggplot(raw5, aes(x=factor(QUARTILE), y=values, fill=SPP)) +
geom_boxplot()
######BASINS#####
A4.lat <- aov(values~BASIN, data=lat.raw5)
summary(A4.lat)## Df Sum Sq Mean Sq F value Pr(>F)
## BASIN 5 0.8 0.1597 0.856 0.51
## Residuals 2138 398.7 0.1865A4.form <- aov(values~BASIN, data=form.raw5)
summary(A4.form)## Df Sum Sq Mean Sq F value Pr(>F)
## BASIN 4 0.6 0.1525 0.698 0.593
## Residuals 2651 579.3 0.2185#between species
A4 <- aov(values~BASIN*SPP, data=raw5)
summary(A4)## Df Sum Sq Mean Sq F value Pr(>F)
## BASIN 6 0.6 0.09760 0.478 0.825
## SPP 1 0.0 0.03245 0.159 0.690
## BASIN:SPP 3 0.8 0.27201 1.332 0.262
## Residuals 4789 978.0 0.20422ggplot(raw5, aes(x=factor(BASIN), y=values, fill=SPP)) +
geom_boxplot()
#####WATERSHEDS#####
A5.lat <- aov(values~WATERSHED, data=lat.raw5)
summary(A5.lat)## Df Sum Sq Mean Sq F value Pr(>F)
## WATERSHED 11 2.7 0.2441 1.312 0.211
## Residuals 2132 396.8 0.1861A5.form <- aov(values~WATERSHED, data=form.raw5)
summary(A5.form)## Df Sum Sq Mean Sq F value Pr(>F)
## WATERSHED 7 5.9 0.8383 3.867 0.000339 ***
## Residuals 2648 574.0 0.2168
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1#between species
A5 <- aov(values~WATERSHED*SPP, data=raw5)
summary(A5)## Df Sum Sq Mean Sq F value Pr(>F)
## WATERSHED 13 5.9 0.4574 2.252 0.00609 **
## SPP 1 0.2 0.1715 0.844 0.35818
## WATERSHED:SPP 5 2.5 0.4924 2.424 0.03332 *
## Residuals 4780 970.8 0.2031
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1ggplot(raw5, aes(x=factor(WATERSHED), y=values, fill=SPP)) +
geom_boxplot()
GLMMs
Will run mixed models with zones/basins/watersheds as random effect. This will account for any variation seen at these levels and show us if there are any consistent species differences. Can only do this with residuals.
Zones
library(lme4)## Loading required package: Matrixlibrary(lmerTest)##
## Attaching package: 'lmerTest'## The following object is masked from 'package:lme4':
##
## lmer## The following object is masked from 'package:stats':
##
## stepMM.D <- glmer(abs.res.D ~ SPP + (1|QUARTILE), data=raw3)#originally had family=poisson, since this is count data, but because this was the residuals of count data, the values were non-integers and poisson only deals with integers. ## Warning in glmer(abs.res.D ~ SPP + (1 | QUARTILE), data = raw3): calling
## glmer() with family=gaussian (identity link) as a shortcut to lmer() is
## deprecated; please call lmer() directly## boundary (singular) fit: see help('isSingular')MM.D.a <- anova(MM.D, test="Chisq")## Warning in anova.merMod(MM.D, test = "Chisq"): additional arguments ignored:
## 'test'summary(MM.D.a)## npar Sum Sq Mean Sq F value
## Min. :1 Min. :0.06351 Min. :0.06351 Min. :0.3854
## 1st Qu.:1 1st Qu.:0.06351 1st Qu.:0.06351 1st Qu.:0.3854
## Median :1 Median :0.06351 Median :0.06351 Median :0.3854
## Mean :1 Mean :0.06351 Mean :0.06351 Mean :0.3854
## 3rd Qu.:1 3rd Qu.:0.06351 3rd Qu.:0.06351 3rd Qu.:0.3854
## Max. :1 Max. :0.06351 Max. :0.06351 Max. :0.3854MM.P1 <- glmer(abs.res.P1 ~ SPP+ (1|QUARTILE), data=raw3)## Warning in glmer(abs.res.P1 ~ SPP + (1 | QUARTILE), data = raw3): calling
## glmer() with family=gaussian (identity link) as a shortcut to lmer() is
## deprecated; please call lmer() directlyMM.P1.a <- anova(MM.P1, test="Chisq")## Warning in anova.merMod(MM.P1, test = "Chisq"): additional arguments ignored:
## 'test'summary(MM.P1.a)## npar Sum Sq Mean Sq F value
## Min. :1 Min. :0.3631 Min. :0.3631 Min. :1.956
## 1st Qu.:1 1st Qu.:0.3631 1st Qu.:0.3631 1st Qu.:1.956
## Median :1 Median :0.3631 Median :0.3631 Median :1.956
## Mean :1 Mean :0.3631 Mean :0.3631 Mean :1.956
## 3rd Qu.:1 3rd Qu.:0.3631 3rd Qu.:0.3631 3rd Qu.:1.956
## Max. :1 Max. :0.3631 Max. :0.3631 Max. :1.956MM.P1.R <- glmer(abs.res.P1.R ~ SPP+ (1|QUARTILE), data=raw3)## Warning in glmer(abs.res.P1.R ~ SPP + (1 | QUARTILE), data = raw3): calling
## glmer() with family=gaussian (identity link) as a shortcut to lmer() is
## deprecated; please call lmer() directly## boundary (singular) fit: see help('isSingular')MM.P1.Ra <- anova(MM.P1.R, test="Chisq")## Warning in anova.merMod(MM.P1.R, test = "Chisq"): additional arguments ignored:
## 'test'summary(MM.P1.Ra)## npar Sum Sq Mean Sq F value
## Min. :1 Min. :1.798 Min. :1.798 Min. :11.61
## 1st Qu.:1 1st Qu.:1.798 1st Qu.:1.798 1st Qu.:11.61
## Median :1 Median :1.798 Median :1.798 Median :11.61
## Mean :1 Mean :1.798 Mean :1.798 Mean :11.61
## 3rd Qu.:1 3rd Qu.:1.798 3rd Qu.:1.798 3rd Qu.:11.61
## Max. :1 Max. :1.798 Max. :1.798 Max. :11.61MM.LLSC <- glmer(abs.res.LLSC ~ SPP+ (1|QUARTILE), data=raw3)## Warning in glmer(abs.res.LLSC ~ SPP + (1 | QUARTILE), data = raw3): calling
## glmer() with family=gaussian (identity link) as a shortcut to lmer() is
## deprecated; please call lmer() directly## boundary (singular) fit: see help('isSingular')MM.LLSC.a <- anova(MM.LLSC, test="Chisq")## Warning in anova.merMod(MM.LLSC, test = "Chisq"): additional arguments ignored:
## 'test'summary(MM.LLSC.a)## npar Sum Sq Mean Sq F value
## Min. :1 Min. :1.401 Min. :1.401 Min. :2.901
## 1st Qu.:1 1st Qu.:1.401 1st Qu.:1.401 1st Qu.:2.901
## Median :1 Median :1.401 Median :1.401 Median :2.901
## Mean :1 Mean :1.401 Mean :1.401 Mean :2.901
## 3rd Qu.:1 3rd Qu.:1.401 3rd Qu.:1.401 3rd Qu.:2.901
## Max. :1 Max. :1.401 Max. :1.401 Max. :2.901MM.SBLL <- glmer(abs.res.SBLL ~ SPP+ (1|QUARTILE), data=raw3)## Warning in glmer(abs.res.SBLL ~ SPP + (1 | QUARTILE), data = raw3): calling
## glmer() with family=gaussian (identity link) as a shortcut to lmer() is
## deprecated; please call lmer() directlyMM.SBLL.a <- anova(MM.SBLL, test="Chisq")## Warning in anova.merMod(MM.SBLL, test = "Chisq"): additional arguments ignored:
## 'test'summary(MM.SBLL.a)## npar Sum Sq Mean Sq F value
## Min. :1 Min. :0.5775 Min. :0.5775 Min. :4.335
## 1st Qu.:1 1st Qu.:0.5775 1st Qu.:0.5775 1st Qu.:4.335
## Median :1 Median :0.5775 Median :0.5775 Median :4.335
## Mean :1 Mean :0.5775 Mean :0.5775 Mean :4.335
## 3rd Qu.:1 3rd Qu.:0.5775 3rd Qu.:0.5775 3rd Qu.:4.335
## Max. :1 Max. :0.5775 Max. :0.5775 Max. :4.335MM.BD <- glmer(abs.res.BD ~ SPP+ (1|QUARTILE), data=raw3)## Warning in glmer(abs.res.BD ~ SPP + (1 | QUARTILE), data = raw3): calling
## glmer() with family=gaussian (identity link) as a shortcut to lmer() is
## deprecated; please call lmer() directly## boundary (singular) fit: see help('isSingular')MM.BD.a <- anova(MM.BD, test="Chisq")## Warning in anova.merMod(MM.BD, test = "Chisq"): additional arguments ignored:
## 'test'summary(MM.BD.a)## npar Sum Sq Mean Sq F value
## Min. :1 Min. :3.461e-05 Min. :3.461e-05 Min. :0.02562
## 1st Qu.:1 1st Qu.:3.461e-05 1st Qu.:3.461e-05 1st Qu.:0.02562
## Median :1 Median :3.461e-05 Median :3.461e-05 Median :0.02562
## Mean :1 Mean :3.461e-05 Mean :3.461e-05 Mean :0.02562
## 3rd Qu.:1 3rd Qu.:3.461e-05 3rd Qu.:3.461e-05 3rd Qu.:0.02562
## Max. :1 Max. :3.461e-05 Max. :3.461e-05 Max. :0.02562MM.CPD <- glmer(abs.res.CPD ~ SPP+ (1|QUARTILE), data=raw3)## Warning in glmer(abs.res.CPD ~ SPP + (1 | QUARTILE), data = raw3): calling
## glmer() with family=gaussian (identity link) as a shortcut to lmer() is
## deprecated; please call lmer() directlyMM.CPD.a <- anova(MM.CPD, test="Chisq")## Warning in anova.merMod(MM.CPD, test = "Chisq"): additional arguments ignored:
## 'test'summary(MM.CPD.a)## npar Sum Sq Mean Sq F value
## Min. :1 Min. :0.001722 Min. :0.001722 Min. :2.627
## 1st Qu.:1 1st Qu.:0.001722 1st Qu.:0.001722 1st Qu.:2.627
## Median :1 Median :0.001722 Median :0.001722 Median :2.627
## Mean :1 Mean :0.001722 Mean :0.001722 Mean :2.627
## 3rd Qu.:1 3rd Qu.:0.001722 3rd Qu.:0.001722 3rd Qu.:2.627
## Max. :1 Max. :0.001722 Max. :0.001722 Max. :2.627MM.CPL <- glmer(abs.res.CPL ~ SPP+ (1|QUARTILE), data=raw3)## Warning in glmer(abs.res.CPL ~ SPP + (1 | QUARTILE), data = raw3): calling
## glmer() with family=gaussian (identity link) as a shortcut to lmer() is
## deprecated; please call lmer() directlyMM.CPL.a <- anova(MM.CPL, test="Chisq")## Warning in anova.merMod(MM.CPL, test = "Chisq"): additional arguments ignored:
## 'test'summary(MM.CPL.a)## npar Sum Sq Mean Sq F value
## Min. :1 Min. :0.0004791 Min. :0.0004791 Min. :0.5381
## 1st Qu.:1 1st Qu.:0.0004791 1st Qu.:0.0004791 1st Qu.:0.5381
## Median :1 Median :0.0004791 Median :0.0004791 Median :0.5381
## Mean :1 Mean :0.0004791 Mean :0.0004791 Mean :0.5381
## 3rd Qu.:1 3rd Qu.:0.0004791 3rd Qu.:0.0004791 3rd Qu.:0.5381
## Max. :1 Max. :0.0004791 Max. :0.0004791 Max. :0.5381MM.PreDL <- glmer(abs.res.PreDL ~ SPP+ (1|QUARTILE), data=raw3)## Warning in glmer(abs.res.PreDL ~ SPP + (1 | QUARTILE), data = raw3): calling
## glmer() with family=gaussian (identity link) as a shortcut to lmer() is
## deprecated; please call lmer() directlyMM.PreDL.a <- anova(MM.PreDL, test="Chisq")## Warning in anova.merMod(MM.PreDL, test = "Chisq"): additional arguments
## ignored: 'test'summary(MM.PreDL.a)## npar Sum Sq Mean Sq F value
## Min. :1 Min. :2.76e-05 Min. :2.76e-05 Min. :0.06634
## 1st Qu.:1 1st Qu.:2.76e-05 1st Qu.:2.76e-05 1st Qu.:0.06634
## Median :1 Median :2.76e-05 Median :2.76e-05 Median :0.06634
## Mean :1 Mean :2.76e-05 Mean :2.76e-05 Mean :0.06634
## 3rd Qu.:1 3rd Qu.:2.76e-05 3rd Qu.:2.76e-05 3rd Qu.:0.06634
## Max. :1 Max. :2.76e-05 Max. :2.76e-05 Max. :0.06634MM.DbL <- glmer(abs.res.DbL ~ SPP+ (1|QUARTILE), data=raw3)## Warning in glmer(abs.res.DbL ~ SPP + (1 | QUARTILE), data = raw3): calling
## glmer() with family=gaussian (identity link) as a shortcut to lmer() is
## deprecated; please call lmer() directlyMM.DbL.a <- anova(MM.DbL, test="Chisq")## Warning in anova.merMod(MM.DbL, test = "Chisq"): additional arguments ignored:
## 'test'summary(MM.DbL.a)## npar Sum Sq Mean Sq F value
## Min. :1 Min. :4.269e-05 Min. :4.269e-05 Min. :0.02331
## 1st Qu.:1 1st Qu.:4.269e-05 1st Qu.:4.269e-05 1st Qu.:0.02331
## Median :1 Median :4.269e-05 Median :4.269e-05 Median :0.02331
## Mean :1 Mean :4.269e-05 Mean :4.269e-05 Mean :0.02331
## 3rd Qu.:1 3rd Qu.:4.269e-05 3rd Qu.:4.269e-05 3rd Qu.:0.02331
## Max. :1 Max. :4.269e-05 Max. :4.269e-05 Max. :0.02331MM.HL <- glmer(abs.res.HL ~ SPP+ (1|QUARTILE), data=raw3)## Warning in glmer(abs.res.HL ~ SPP + (1 | QUARTILE), data = raw3): calling
## glmer() with family=gaussian (identity link) as a shortcut to lmer() is
## deprecated; please call lmer() directlyMM.HL.a <- anova(MM.HL, test="Chisq")## Warning in anova.merMod(MM.HL, test = "Chisq"): additional arguments ignored:
## 'test'summary(MM.HL.a)## npar Sum Sq Mean Sq F value
## Min. :1 Min. :0.001879 Min. :0.001879 Min. :1.941
## 1st Qu.:1 1st Qu.:0.001879 1st Qu.:0.001879 1st Qu.:1.941
## Median :1 Median :0.001879 Median :0.001879 Median :1.941
## Mean :1 Mean :0.001879 Mean :0.001879 Mean :1.941
## 3rd Qu.:1 3rd Qu.:0.001879 3rd Qu.:0.001879 3rd Qu.:1.941
## Max. :1 Max. :0.001879 Max. :0.001879 Max. :1.941MM.HD <- glmer(abs.res.HD ~ SPP+ (1|QUARTILE), data=raw3)## Warning in glmer(abs.res.HD ~ SPP + (1 | QUARTILE), data = raw3): calling
## glmer() with family=gaussian (identity link) as a shortcut to lmer() is
## deprecated; please call lmer() directlyMM.HD.a <- anova(MM.HD, test="Chisq")## Warning in anova.merMod(MM.HD, test = "Chisq"): additional arguments ignored:
## 'test'summary(MM.HD.a)## npar Sum Sq Mean Sq F value
## Min. :1 Min. :1.701e-06 Min. :1.701e-06 Min. :0.001735
## 1st Qu.:1 1st Qu.:1.701e-06 1st Qu.:1.701e-06 1st Qu.:0.001735
## Median :1 Median :1.701e-06 Median :1.701e-06 Median :0.001735
## Mean :1 Mean :1.701e-06 Mean :1.701e-06 Mean :0.001735
## 3rd Qu.:1 3rd Qu.:1.701e-06 3rd Qu.:1.701e-06 3rd Qu.:0.001735
## Max. :1 Max. :1.701e-06 Max. :1.701e-06 Max. :0.001735MM.HW <- glmer(abs.res.HW ~ SPP+ (1|QUARTILE), data=raw3)## Warning in glmer(abs.res.HW ~ SPP + (1 | QUARTILE), data = raw3): calling
## glmer() with family=gaussian (identity link) as a shortcut to lmer() is
## deprecated; please call lmer() directlyMM.HW.a <- anova(MM.HW, test="Chisq")## Warning in anova.merMod(MM.HW, test = "Chisq"): additional arguments ignored:
## 'test'summary(MM.HW.a)## npar Sum Sq Mean Sq F value
## Min. :1 Min. :0.002504 Min. :0.002504 Min. :3.287
## 1st Qu.:1 1st Qu.:0.002504 1st Qu.:0.002504 1st Qu.:3.287
## Median :1 Median :0.002504 Median :0.002504 Median :3.287
## Mean :1 Mean :0.002504 Mean :0.002504 Mean :3.287
## 3rd Qu.:1 3rd Qu.:0.002504 3rd Qu.:0.002504 3rd Qu.:3.287
## Max. :1 Max. :0.002504 Max. :0.002504 Max. :3.287MM.SnL <- glmer(abs.res.SnL ~ SPP+ (1|QUARTILE), data=raw3)## Warning in glmer(abs.res.SnL ~ SPP + (1 | QUARTILE), data = raw3): calling
## glmer() with family=gaussian (identity link) as a shortcut to lmer() is
## deprecated; please call lmer() directlyMM.SnL.a <- anova(MM.SnL, test="Chisq")## Warning in anova.merMod(MM.SnL, test = "Chisq"): additional arguments ignored:
## 'test'summary(MM.SnL.a)## npar Sum Sq Mean Sq F value
## Min. :1 Min. :0.0005063 Min. :0.0005063 Min. :0.8551
## 1st Qu.:1 1st Qu.:0.0005063 1st Qu.:0.0005063 1st Qu.:0.8551
## Median :1 Median :0.0005063 Median :0.0005063 Median :0.8551
## Mean :1 Mean :0.0005063 Mean :0.0005063 Mean :0.8551
## 3rd Qu.:1 3rd Qu.:0.0005063 3rd Qu.:0.0005063 3rd Qu.:0.8551
## Max. :1 Max. :0.0005063 Max. :0.0005063 Max. :0.8551MM.OL <- glmer(abs.res.OL ~ SPP+ (1|QUARTILE), data=raw3)## Warning in glmer(abs.res.OL ~ SPP + (1 | QUARTILE), data = raw3): calling
## glmer() with family=gaussian (identity link) as a shortcut to lmer() is
## deprecated; please call lmer() directlyMM.OL.a <- anova(MM.OL, test="Chisq")## Warning in anova.merMod(MM.OL, test = "Chisq"): additional arguments ignored:
## 'test'summary(MM.OL.a)## npar Sum Sq Mean Sq F value
## Min. :1 Min. :4.43e-33 Min. :4.43e-33 Min. :1.904
## 1st Qu.:1 1st Qu.:4.43e-33 1st Qu.:4.43e-33 1st Qu.:1.904
## Median :1 Median :4.43e-33 Median :4.43e-33 Median :1.904
## Mean :1 Mean :4.43e-33 Mean :4.43e-33 Mean :1.904
## 3rd Qu.:1 3rd Qu.:4.43e-33 3rd Qu.:4.43e-33 3rd Qu.:1.904
## Max. :1 Max. :4.43e-33 Max. :4.43e-33 Max. :1.904Watershed nested in Basin
MM1.D <- glmer(abs.res.D ~ SPP + (1|BASIN/WATERSHED), data=raw3)## Warning in glmer(abs.res.D ~ SPP + (1 | BASIN/WATERSHED), data = raw3): calling
## glmer() with family=gaussian (identity link) as a shortcut to lmer() is
## deprecated; please call lmer() directlyMM1.D.a <- anova(MM1.D, test="Chisq")## Warning in anova.merMod(MM1.D, test = "Chisq"): additional arguments ignored:
## 'test'summary(MM1.D.a)## npar Sum Sq Mean Sq F value
## Min. :1 Min. :0.01821 Min. :0.01821 Min. :0.1157
## 1st Qu.:1 1st Qu.:0.01821 1st Qu.:0.01821 1st Qu.:0.1157
## Median :1 Median :0.01821 Median :0.01821 Median :0.1157
## Mean :1 Mean :0.01821 Mean :0.01821 Mean :0.1157
## 3rd Qu.:1 3rd Qu.:0.01821 3rd Qu.:0.01821 3rd Qu.:0.1157
## Max. :1 Max. :0.01821 Max. :0.01821 Max. :0.1157MM1.P1 <- glmer(abs.res.P1 ~ SPP+ (1|BASIN/WATERSHED), data=raw3)## Warning in glmer(abs.res.P1 ~ SPP + (1 | BASIN/WATERSHED), data = raw3):
## calling glmer() with family=gaussian (identity link) as a shortcut to lmer() is
## deprecated; please call lmer() directly## boundary (singular) fit: see help('isSingular')MM1.P1.a <- anova(MM1.P1, test="Chisq")## Warning in anova.merMod(MM1.P1, test = "Chisq"): additional arguments ignored:
## 'test'summary(MM1.P1.a)## npar Sum Sq Mean Sq F value
## Min. :1 Min. :0.2476 Min. :0.2476 Min. :1.363
## 1st Qu.:1 1st Qu.:0.2476 1st Qu.:0.2476 1st Qu.:1.363
## Median :1 Median :0.2476 Median :0.2476 Median :1.363
## Mean :1 Mean :0.2476 Mean :0.2476 Mean :1.363
## 3rd Qu.:1 3rd Qu.:0.2476 3rd Qu.:0.2476 3rd Qu.:1.363
## Max. :1 Max. :0.2476 Max. :0.2476 Max. :1.363MM1.P1.R <- glmer(abs.res.P1.R ~ SPP+ (1|BASIN/WATERSHED), data=raw3)## Warning in glmer(abs.res.P1.R ~ SPP + (1 | BASIN/WATERSHED), data = raw3):
## calling glmer() with family=gaussian (identity link) as a shortcut to lmer() is
## deprecated; please call lmer() directly## boundary (singular) fit: see help('isSingular')MM1.P1.Ra <- anova(MM1.P1.R, test="Chisq")## Warning in anova.merMod(MM1.P1.R, test = "Chisq"): additional arguments
## ignored: 'test'summary(MM1.P1.Ra)## npar Sum Sq Mean Sq F value
## Min. :1 Min. :1.798 Min. :1.798 Min. :11.61
## 1st Qu.:1 1st Qu.:1.798 1st Qu.:1.798 1st Qu.:11.61
## Median :1 Median :1.798 Median :1.798 Median :11.61
## Mean :1 Mean :1.798 Mean :1.798 Mean :11.61
## 3rd Qu.:1 3rd Qu.:1.798 3rd Qu.:1.798 3rd Qu.:11.61
## Max. :1 Max. :1.798 Max. :1.798 Max. :11.61MM1.LLSC <- glmer(abs.res.LLSC ~ SPP+ (1|BASIN/WATERSHED), data=raw3)## Warning in glmer(abs.res.LLSC ~ SPP + (1 | BASIN/WATERSHED), data = raw3):
## calling glmer() with family=gaussian (identity link) as a shortcut to lmer() is
## deprecated; please call lmer() directly## boundary (singular) fit: see help('isSingular')MM1.LLSC.a <- anova(MM1.LLSC, test="Chisq")## Warning in anova.merMod(MM1.LLSC, test = "Chisq"): additional arguments
## ignored: 'test'summary(MM1.LLSC.a)## npar Sum Sq Mean Sq F value
## Min. :1 Min. :0.8627 Min. :0.8627 Min. :2
## 1st Qu.:1 1st Qu.:0.8627 1st Qu.:0.8627 1st Qu.:2
## Median :1 Median :0.8627 Median :0.8627 Median :2
## Mean :1 Mean :0.8627 Mean :0.8627 Mean :2
## 3rd Qu.:1 3rd Qu.:0.8627 3rd Qu.:0.8627 3rd Qu.:2
## Max. :1 Max. :0.8627 Max. :0.8627 Max. :2MM1.SBLL <- glmer(abs.res.SBLL ~ SPP+ (1|BASIN/WATERSHED), data=raw3)## Warning in glmer(abs.res.SBLL ~ SPP + (1 | BASIN/WATERSHED), data = raw3):
## calling glmer() with family=gaussian (identity link) as a shortcut to lmer() is
## deprecated; please call lmer() directly## boundary (singular) fit: see help('isSingular')MM1.SBLL.a <- anova(MM1.SBLL, test="Chisq")## Warning in anova.merMod(MM1.SBLL, test = "Chisq"): additional arguments
## ignored: 'test'summary(MM1.SBLL.a)## npar Sum Sq Mean Sq F value
## Min. :1 Min. :0.3889 Min. :0.3889 Min. :2.989
## 1st Qu.:1 1st Qu.:0.3889 1st Qu.:0.3889 1st Qu.:2.989
## Median :1 Median :0.3889 Median :0.3889 Median :2.989
## Mean :1 Mean :0.3889 Mean :0.3889 Mean :2.989
## 3rd Qu.:1 3rd Qu.:0.3889 3rd Qu.:0.3889 3rd Qu.:2.989
## Max. :1 Max. :0.3889 Max. :0.3889 Max. :2.989MM1.BD <- glmer(abs.res.BD ~ SPP+ (1|BASIN/WATERSHED), data=raw3)## Warning in glmer(abs.res.BD ~ SPP + (1 | BASIN/WATERSHED), data = raw3):
## calling glmer() with family=gaussian (identity link) as a shortcut to lmer() is
## deprecated; please call lmer() directlyMM1.BD.a <- anova(MM1.BD, test="Chisq")## Warning in anova.merMod(MM1.BD, test = "Chisq"): additional arguments ignored:
## 'test'summary(MM1.BD.a)## npar Sum Sq Mean Sq F value
## Min. :1 Min. :0.0009062 Min. :0.0009062 Min. :0.7214
## 1st Qu.:1 1st Qu.:0.0009062 1st Qu.:0.0009062 1st Qu.:0.7214
## Median :1 Median :0.0009062 Median :0.0009062 Median :0.7214
## Mean :1 Mean :0.0009062 Mean :0.0009062 Mean :0.7214
## 3rd Qu.:1 3rd Qu.:0.0009062 3rd Qu.:0.0009062 3rd Qu.:0.7214
## Max. :1 Max. :0.0009062 Max. :0.0009062 Max. :0.7214MM1.CPD <- glmer(abs.res.CPD ~ SPP+ (1|BASIN/WATERSHED), data=raw3)## Warning in glmer(abs.res.CPD ~ SPP + (1 | BASIN/WATERSHED), data = raw3):
## calling glmer() with family=gaussian (identity link) as a shortcut to lmer() is
## deprecated; please call lmer() directly## boundary (singular) fit: see help('isSingular')MM1.CPD.a <- anova(MM1.CPD, test="Chisq")## Warning in anova.merMod(MM1.CPD, test = "Chisq"): additional arguments ignored:
## 'test'summary(MM1.CPD.a)## npar Sum Sq Mean Sq F value
## Min. :1 Min. :0.001731 Min. :0.001731 Min. :2.71
## 1st Qu.:1 1st Qu.:0.001731 1st Qu.:0.001731 1st Qu.:2.71
## Median :1 Median :0.001731 Median :0.001731 Median :2.71
## Mean :1 Mean :0.001731 Mean :0.001731 Mean :2.71
## 3rd Qu.:1 3rd Qu.:0.001731 3rd Qu.:0.001731 3rd Qu.:2.71
## Max. :1 Max. :0.001731 Max. :0.001731 Max. :2.71MM1.CPL <- glmer(abs.res.CPL ~ SPP+ (1|BASIN/WATERSHED), data=raw3)## Warning in glmer(abs.res.CPL ~ SPP + (1 | BASIN/WATERSHED), data = raw3):
## calling glmer() with family=gaussian (identity link) as a shortcut to lmer() is
## deprecated; please call lmer() directlyMM1.CPL.a <- anova(MM1.CPL, test="Chisq")## Warning in anova.merMod(MM1.CPL, test = "Chisq"): additional arguments ignored:
## 'test'summary(MM1.CPL.a)## npar Sum Sq Mean Sq F value
## Min. :1 Min. :0.0002359 Min. :0.0002359 Min. :0.2876
## 1st Qu.:1 1st Qu.:0.0002359 1st Qu.:0.0002359 1st Qu.:0.2876
## Median :1 Median :0.0002359 Median :0.0002359 Median :0.2876
## Mean :1 Mean :0.0002359 Mean :0.0002359 Mean :0.2876
## 3rd Qu.:1 3rd Qu.:0.0002359 3rd Qu.:0.0002359 3rd Qu.:0.2876
## Max. :1 Max. :0.0002359 Max. :0.0002359 Max. :0.2876MM1.PreDL <- glmer(abs.res.PreDL ~ SPP+ (1|BASIN/WATERSHED), data=raw3)## Warning in glmer(abs.res.PreDL ~ SPP + (1 | BASIN/WATERSHED), data = raw3):
## calling glmer() with family=gaussian (identity link) as a shortcut to lmer() is
## deprecated; please call lmer() directlyMM1.PreDL.a <- anova(MM1.PreDL, test="Chisq")## Warning in anova.merMod(MM1.PreDL, test = "Chisq"): additional arguments
## ignored: 'test'summary(MM1.PreDL.a)## npar Sum Sq Mean Sq F value
## Min. :1 Min. :0.0004071 Min. :0.0004071 Min. :1.007
## 1st Qu.:1 1st Qu.:0.0004071 1st Qu.:0.0004071 1st Qu.:1.007
## Median :1 Median :0.0004071 Median :0.0004071 Median :1.007
## Mean :1 Mean :0.0004071 Mean :0.0004071 Mean :1.007
## 3rd Qu.:1 3rd Qu.:0.0004071 3rd Qu.:0.0004071 3rd Qu.:1.007
## Max. :1 Max. :0.0004071 Max. :0.0004071 Max. :1.007MM1.DbL <- glmer(abs.res.DbL ~ SPP+ (1|BASIN/WATERSHED), data=raw3)## Warning in glmer(abs.res.DbL ~ SPP + (1 | BASIN/WATERSHED), data = raw3):
## calling glmer() with family=gaussian (identity link) as a shortcut to lmer() is
## deprecated; please call lmer() directly## boundary (singular) fit: see help('isSingular')MM1.DbL.a <- anova(MM1.DbL, test="Chisq")## Warning in anova.merMod(MM1.DbL, test = "Chisq"): additional arguments ignored:
## 'test'summary(MM1.DbL.a)## npar Sum Sq Mean Sq F value
## Min. :1 Min. :0.0003223 Min. :0.0003223 Min. :0.1812
## 1st Qu.:1 1st Qu.:0.0003223 1st Qu.:0.0003223 1st Qu.:0.1812
## Median :1 Median :0.0003223 Median :0.0003223 Median :0.1812
## Mean :1 Mean :0.0003223 Mean :0.0003223 Mean :0.1812
## 3rd Qu.:1 3rd Qu.:0.0003223 3rd Qu.:0.0003223 3rd Qu.:0.1812
## Max. :1 Max. :0.0003223 Max. :0.0003223 Max. :0.1812MM1.HL <- glmer(abs.res.HL ~ SPP+ (1|BASIN/WATERSHED), data=raw3)## Warning in glmer(abs.res.HL ~ SPP + (1 | BASIN/WATERSHED), data = raw3):
## calling glmer() with family=gaussian (identity link) as a shortcut to lmer() is
## deprecated; please call lmer() directly## boundary (singular) fit: see help('isSingular')MM1.HL.a <- anova(MM1.HL, test="Chisq")## Warning in anova.merMod(MM1.HL, test = "Chisq"): additional arguments ignored:
## 'test'summary(MM1.HL.a)## npar Sum Sq Mean Sq F value
## Min. :1 Min. :3.697e-05 Min. :3.697e-05 Min. :0.04111
## 1st Qu.:1 1st Qu.:3.697e-05 1st Qu.:3.697e-05 1st Qu.:0.04111
## Median :1 Median :3.697e-05 Median :3.697e-05 Median :0.04111
## Mean :1 Mean :3.697e-05 Mean :3.697e-05 Mean :0.04111
## 3rd Qu.:1 3rd Qu.:3.697e-05 3rd Qu.:3.697e-05 3rd Qu.:0.04111
## Max. :1 Max. :3.697e-05 Max. :3.697e-05 Max. :0.04111MM1.HD <- glmer(abs.res.HD ~ SPP+ (1|BASIN/WATERSHED), data=raw3)## Warning in glmer(abs.res.HD ~ SPP + (1 | BASIN/WATERSHED), data = raw3):
## calling glmer() with family=gaussian (identity link) as a shortcut to lmer() is
## deprecated; please call lmer() directly## boundary (singular) fit: see help('isSingular')MM1.HD.a <- anova(MM1.HD, test="Chisq")## Warning in anova.merMod(MM1.HD, test = "Chisq"): additional arguments ignored:
## 'test'summary(MM1.HD.a)## npar Sum Sq Mean Sq F value
## Min. :1 Min. :9.321e-06 Min. :9.321e-06 Min. :0.009664
## 1st Qu.:1 1st Qu.:9.321e-06 1st Qu.:9.321e-06 1st Qu.:0.009664
## Median :1 Median :9.321e-06 Median :9.321e-06 Median :0.009664
## Mean :1 Mean :9.321e-06 Mean :9.321e-06 Mean :0.009664
## 3rd Qu.:1 3rd Qu.:9.321e-06 3rd Qu.:9.321e-06 3rd Qu.:0.009664
## Max. :1 Max. :9.321e-06 Max. :9.321e-06 Max. :0.009664MM1.HW <- glmer(abs.res.HW ~ SPP+ (1|BASIN/WATERSHED), data=raw3)## Warning in glmer(abs.res.HW ~ SPP + (1 | BASIN/WATERSHED), data = raw3):
## calling glmer() with family=gaussian (identity link) as a shortcut to lmer() is
## deprecated; please call lmer() directlyMM1.HW.a <- anova(MM1.HW, test="Chisq")## Warning in anova.merMod(MM1.HW, test = "Chisq"): additional arguments ignored:
## 'test'summary(MM1.HW.a)## npar Sum Sq Mean Sq F value
## Min. :1 Min. :0.004251 Min. :0.004251 Min. :5.681
## 1st Qu.:1 1st Qu.:0.004251 1st Qu.:0.004251 1st Qu.:5.681
## Median :1 Median :0.004251 Median :0.004251 Median :5.681
## Mean :1 Mean :0.004251 Mean :0.004251 Mean :5.681
## 3rd Qu.:1 3rd Qu.:0.004251 3rd Qu.:0.004251 3rd Qu.:5.681
## Max. :1 Max. :0.004251 Max. :0.004251 Max. :5.681MM1.SnL <- glmer(abs.res.SnL ~ SPP+ (1|BASIN/WATERSHED), data=raw3)## Warning in glmer(abs.res.SnL ~ SPP + (1 | BASIN/WATERSHED), data = raw3):
## calling glmer() with family=gaussian (identity link) as a shortcut to lmer() is
## deprecated; please call lmer() directlyMM1.SnL.a <- anova(MM1.SnL, test="Chisq")## Warning in anova.merMod(MM1.SnL, test = "Chisq"): additional arguments ignored:
## 'test'summary(MM1.SnL.a)## npar Sum Sq Mean Sq F value
## Min. :1 Min. :0.0003137 Min. :0.0003137 Min. :0.5899
## 1st Qu.:1 1st Qu.:0.0003137 1st Qu.:0.0003137 1st Qu.:0.5899
## Median :1 Median :0.0003137 Median :0.0003137 Median :0.5899
## Mean :1 Mean :0.0003137 Mean :0.0003137 Mean :0.5899
## 3rd Qu.:1 3rd Qu.:0.0003137 3rd Qu.:0.0003137 3rd Qu.:0.5899
## Max. :1 Max. :0.0003137 Max. :0.0003137 Max. :0.5899MM1.OL <- glmer(abs.res.OL ~ SPP+ (1|BASIN/WATERSHED), data=raw3)## Warning in glmer(abs.res.OL ~ SPP + (1 | BASIN/WATERSHED), data = raw3):
## calling glmer() with family=gaussian (identity link) as a shortcut to lmer() is
## deprecated; please call lmer() directlyMM1.OL.a <- anova(MM1.OL, test="Chisq")## Warning in anova.merMod(MM1.OL, test = "Chisq"): additional arguments ignored:
## 'test'summary(MM1.OL.a)## npar Sum Sq Mean Sq F value
## Min. :1 Min. :3.795e-33 Min. :3.795e-33 Min. :1.62
## 1st Qu.:1 1st Qu.:3.795e-33 1st Qu.:3.795e-33 1st Qu.:1.62
## Median :1 Median :3.795e-33 Median :3.795e-33 Median :1.62
## Mean :1 Mean :3.795e-33 Mean :3.795e-33 Mean :1.62
## 3rd Qu.:1 3rd Qu.:3.795e-33 3rd Qu.:3.795e-33 3rd Qu.:1.62
## Max. :1 Max. :3.795e-33 Max. :3.795e-33 Max. :1.62Levene’s w/ Basin?
Not sure if this is correct, but might try Levene’s test with zone/basin/watershed as an additional independent factor? This is for the traits that did NOT vary with body length.
Zones
library(car)## Loading required package: carData##
## Attaching package: 'car'## The following object is masked from 'package:dplyr':
##
## recode(LT2_P2L <- leveneTest(P2.L~SPP*QUARTILE, data=raw3)) #gives nothing since it's all the same value## Levene's Test for Homogeneity of Variance (center = median)
## Df F value Pr(>F)
## group 7 NaN NaN
## 292(LT2_P2R <- leveneTest(P2.R~SPP*QUARTILE, data=raw3)) #same as above## Levene's Test for Homogeneity of Variance (center = median)
## Df F value Pr(>F)
## group 7 NaN NaN
## 292(LT2_A <- leveneTest(A~SPP*QUARTILE, data=raw3)) ## Levene's Test for Homogeneity of Variance (center = median)
## Df F value Pr(>F)
## group 7 1.0512 0.3954
## 292(LT2_SALL <- leveneTest(SALL~SPP*QUARTILE, data=raw3))## Levene's Test for Homogeneity of Variance (center = median)
## Df F value Pr(>F)
## group 7 10.093 2.613e-11 ***
## 292
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1(LT2_SBLL <- leveneTest(SBLL~SPP*QUARTILE, data=raw3))## Levene's Test for Homogeneity of Variance (center = median)
## Df F value Pr(>F)
## group 7 1.1533 0.3299
## 292(LT2_SBDF <- leveneTest(SBDF~SPP*QUARTILE, data=raw3))## Levene's Test for Homogeneity of Variance (center = median)
## Df F value Pr(>F)
## group 7 2.0714 0.04655 *
## 292
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1(LT2_FLA <- leveneTest(FLA~SPP*QUARTILE, data=raw3))## Levene's Test for Homogeneity of Variance (center = median)
## Df F value Pr(>F)
## group 7 3.5457 0.001129 **
## 292
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1Basins
(LT2_P2L <- leveneTest(P2.L~SPP*BASIN, data=raw3)) #gives nothing since it's all the same value## Levene's Test for Homogeneity of Variance (center = median)
## Df F value Pr(>F)
## group 10 NaN NaN
## 289(LT2_P2R <- leveneTest(P2.R~SPP*BASIN, data=raw3)) #same as above## Levene's Test for Homogeneity of Variance (center = median)
## Df F value Pr(>F)
## group 10 NaN NaN
## 289(LT2_A <- leveneTest(A~SPP*BASIN, data=raw3)) ## Levene's Test for Homogeneity of Variance (center = median)
## Df F value Pr(>F)
## group 10 2.7914 0.002593 **
## 289
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1(LT2_SALL <- leveneTest(SALL~SPP*BASIN, data=raw3))## Levene's Test for Homogeneity of Variance (center = median)
## Df F value Pr(>F)
## group 10 10.224 9.633e-15 ***
## 289
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1(LT2_SBLL <- leveneTest(SBLL~SPP*BASIN, data=raw3))## Levene's Test for Homogeneity of Variance (center = median)
## Df F value Pr(>F)
## group 10 1.467 0.1511
## 289(LT2_SBDF <- leveneTest(SBDF~SPP*BASIN, data=raw3))## Levene's Test for Homogeneity of Variance (center = median)
## Df F value Pr(>F)
## group 10 3.3639 0.0003629 ***
## 289
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1(LT2_FLA <- leveneTest(FLA~SPP*BASIN, data=raw3))## Levene's Test for Homogeneity of Variance (center = median)
## Df F value Pr(>F)
## group 10 1.4055 0.177
## 289Watersheds
(LT2_P2L <- leveneTest(P2.L~SPP*WATERSHED, data=raw3)) #gives nothing since it's all the same value## Levene's Test for Homogeneity of Variance (center = median)
## Df F value Pr(>F)
## group 19 NaN NaN
## 280(LT2_P2R <- leveneTest(P2.R~SPP*WATERSHED, data=raw3)) #same as above## Levene's Test for Homogeneity of Variance (center = median)
## Df F value Pr(>F)
## group 19 NaN NaN
## 280(LT2_A <- leveneTest(A~SPP*WATERSHED, data=raw3)) ## Levene's Test for Homogeneity of Variance (center = median)
## Df F value Pr(>F)
## group 19 1.4755 0.09315 .
## 280
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1(LT2_SALL <- leveneTest(SALL~SPP*WATERSHED, data=raw3))## Levene's Test for Homogeneity of Variance (center = median)
## Df F value Pr(>F)
## group 19 4.7794 1.266e-09 ***
## 280
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1(LT2_SBLL <- leveneTest(SBLL~SPP*WATERSHED, data=raw3))## Levene's Test for Homogeneity of Variance (center = median)
## Df F value Pr(>F)
## group 19 2.0999 0.005256 **
## 280
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1(LT2_SBDF <- leveneTest(SBDF~SPP*WATERSHED, data=raw3))## Levene's Test for Homogeneity of Variance (center = median)
## Df F value Pr(>F)
## group 19 2.0915 0.005484 **
## 280
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1(LT2_FLA <- leveneTest(FLA~SPP*WATERSHED, data=raw3))## Levene's Test for Homogeneity of Variance (center = median)
## Df F value Pr(>F)
## group 19 1.8711 0.01617 *
## 280
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1ICCs
I’m hoping I can do this, but thought another interesting way of testing this would be to calculate and intraclass correlation coefficient–so looking at between-group variance compared to total variance, to see if variation is driven more from within or between group (if there is any at all…). I know lots of examples specify repeated measures, but I think the function below lets me specify that I only have one measurement per subject. I’m going to do this with raw data below, but will also repeat it with PCA scores in the PCA section, so that things are standardized for length. Since I’m interested in variation across populations, I think I would perform this within each sex; I am not sure how I would test this between sexes AND populations for each trait. Maybe I could then compare the ICC scores?
library(psych)
#ICC_result_twoway_explicit <- ICC(data = data\(value, id = data\)composite_id, grouping = data$population, model = “twoway”, type = “agreement”, unit = “single”, r0 = 1)
(ICC_L.D <- ICC(lat3))